According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferen...According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferences and the consistency of expert＇s collating vectors,but they lack of the measure of information similarity.So it may occur that although the collating vector is similar to the group consensus,information uncertainty is great of a certain expert.However,it is clustered to a larger group and given a high weight.For this,a new aggregation method based on entropy and cluster analysis in group decision-making process is provided,in which the collating vectors are classified with information similarity coefficient,and the experts＇ weights are determined according to the result of classification,the entropy of collating vectors and the judgment matrix consistency.Finally,a numerical example shows that the method is feasible and effective.展开更多
For the first time, we used Tullgren method made a study on vertical migrating and cluster analysis of the soil mesofauna in Dongying Halophytes Garden in the Yellow River Delta （YRD）, Shandong Province. The results...For the first time, we used Tullgren method made a study on vertical migrating and cluster analysis of the soil mesofauna in Dongying Halophytes Garden in the Yellow River Delta （YRD）, Shandong Province. The results showed that the soil mesofauna tended to gather on soil surface in most samples at most times, but the vertical migrating greatly varied in different seasons or environment conditions. Acari was the dominant group. The index of diversity of the soil fauna was correlated with the index of evenness. The Acari＇s number of individuals infected other species and numbers. Dominant group-Aeari made greater contribution to the result of cluster analysis, and there were significant differences between communities in different habitats by cluster analysis with both Bray-Curtis and Jaccard similarity coefficient.展开更多
Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the ...Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the length to width, stem girth, dates of budding, leaf yield and ratio of the prime-medium tobacco. The leaf number and the central leaf length showed a positive or a strong positive correlation with the yield per plant. And the leaf number and leaf yield per plant showed a strong positive correlation with the ratio of prime-medium tobacco. The results showed that the leaf yield per plant among these characteristics played a major role in determining the ratio of prime-medium tobacco while the others were less related with the ratio. Square sum of deviation method cluster analyses showed that 24 pure lines of flue-cured tobacco were clustered into two groups. Of the pure lines, Line T1706 and Line T1245 had a far relationship with all other lines, and also had a heterosis when crossed with the other lines. Lines Guangdonghuang 1 and R72（3）B-2-1 were closely related.展开更多
The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was need...The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was needed. The relationship can be deduced by virtual of FEM (Finite Element Method ), ANN (Artificial Neural Network) or MRA (Multiple Regression Analysis). MR A is on the basis of a total understanding of the temperature distribution of th e machine tool. Although the more the temperatures measured are, the more accura te the MRA is, too more temperatures will hinder the analysis calculation. So it is necessary to identify the key temperatures of the machine tool. The selectio n of key temperatures decides the efficiency and precision of MRA. Because of th e complexities and multi-input and multi-output structure of the relationships , the exact quantitative portions as well as the unclear portions must be taken into consideration together to improve the identification of key temperatures. I n this paper, a fuzzy cluster analysis was used to select the key temperatures. The substance of identifying the key temperatures is to group all temperatures b y their relativity, and then to select a temperature from each group as the repr esentation. A fuzzy cluster analysis can uncover the relationships between t he thermal field and deformations more truly and thoroughly. A fuzzy cluster ana lysis is the cluster analysis based on fuzzy sets. Given U={u i|i=0,...,N}, in which u i is the temperature measured, a fuzzy matrix R can be obta ined. The transfer close package t(R) can be deduced from R. A fuzzy clu ster of U then conducts on the basis of t(R). Based on the fuzzy cluster analysis discussed above, this paper identified the k ey temperatures of a horizontal machining center. The number of the temperatures measured was reduced to 4 from 32, and then the multiple regression relationshi p models between the 4 temperatures and the thermal deformations of the spindle were drawn. The remnant errors between the regression models and measured deform ations reached a satisfying low level. At the same time, the decreasing of tempe rature variable number improved the efficiency of measure and analysis greatly.展开更多
Based on structural surface normal vector spherical distance and the pole stereographic projection Euclidean distance,two distance functions were established.The cluster analysis of structure surface was conducted by ...Based on structural surface normal vector spherical distance and the pole stereographic projection Euclidean distance,two distance functions were established.The cluster analysis of structure surface was conducted by the use of ATTA clustering methods based on ant colony piles,and Silhouette index was introduced to evaluate the clustering effect.The clustering analysis of the measured data of Sanshandao Gold Mine shows that ant colony ATTA-based clustering method does better than K-mean clustering analysis.Meanwhile,clustering results of ATTA method based on pole Euclidean distance and ATTA method based on normal vector spherical distance have a great consistence.The clustering results are most close to the pole isopycnic graph.It can efficiently realize grouping of structural plane and determination of the dominant structural surface direction.It is made up for the defects of subjectivity and inaccuracy in icon measurement approach and has great engineering value.展开更多
This paper proposes a suppression method of the deceptive false target(FT) produced by digital radio frequency memory(DRFM) in a multistatic radar system. The simulated deceptive false targets from DRFM cannot be easi...This paper proposes a suppression method of the deceptive false target(FT) produced by digital radio frequency memory(DRFM) in a multistatic radar system. The simulated deceptive false targets from DRFM cannot be easily discriminated and suppressed with traditional radar systems. Therefore, multistatic radar has attracted considerable interest as it provides improved performance against deception jamming due to several separated receivers. This paper first investigates the received signal model in the presence of multiple false targets in all receivers of the multistatic radar. Then, obtain the propagation time delays of the false targets based on the cross-correlation test of the received signals in different receivers. In doing so, local-density-based spatial clustering of applications with noise(LDBSCAN) is proposed to discriminate the FTs from the physical targets(PTs) after compensating the FTs time delays, where the FTs are approximately coincident with one position, while PTs possess small dispersion.Numerical simulations are carried out to demonstrate the feasibility and validness of the proposed method.展开更多
The fuzzy C-means clustering algorithm(FCM) to the fuzzy kernel C-means clustering algorithm(FKCM) to effectively perform cluster analysis on the diversiform structures are extended, such as non-hyperspherical data, d...The fuzzy C-means clustering algorithm(FCM) to the fuzzy kernel C-means clustering algorithm(FKCM) to effectively perform cluster analysis on the diversiform structures are extended, such as non-hyperspherical data, data with noise, data with mixture of heterogeneous cluster prototypes, asymmetric data, etc. Based on the Mercer kernel, FKCM clustering algorithm is derived from FCM algorithm united with kernel method. The results of experiments with the synthetic and real data show that the FKCM clustering algorithm is universality and can effectively unsupervised analyze datasets with variform structures in contrast to FCM algorithm. It is can be imagined that kernel-based clustering algorithm is one of important research direction of fuzzy clustering analysis.展开更多
In this study, we used RAPD to analyze four kinds of color-flowered Salvia splendens Ker-Gawl, and the optimal RAPD reaction conditions were the optimal reaction mixture （25 μL total volume） that contained 2.0 μL ...In this study, we used RAPD to analyze four kinds of color-flowered Salvia splendens Ker-Gawl, and the optimal RAPD reaction conditions were the optimal reaction mixture （25 μL total volume） that contained 2.0 μL 10×buffer, 0.45 mmol·L^-1 dNTPs, 2.0 mmol· L^-1 Mg^2＋, 2 U Taq DNA polymerase, 0.30 umol·L^-2 primer and 40 ng genomic DNA. Total 84 bands were amplified from 12 primers used, and the differential bands had 28 bands, which was 33% of total bands. In cluster group analysis, the four kinds of color-flowered were divided into two styles. One style is that the red color and red-white color were grouped together, then they grouped with purple color into one cluster, and the white color was another style.展开更多
To investigate the judging problem of optimal dividing matrix among several fuzzy dividing matrices in fuzzy dividing space, correspondingly, which is determined by the various choices of cluster samples in the totali...To investigate the judging problem of optimal dividing matrix among several fuzzy dividing matrices in fuzzy dividing space, correspondingly, which is determined by the various choices of cluster samples in the totality sample space, two algorithms are proposed on the basis of the data analysis method in rough sets theory： information system discrete algorithm （algorithm 1） and samples representatives judging algorithm （algorithm 2）. On the principle of the farthest distance, algorithm 1 transforms continuous data into discrete form which could be transacted by rough sets theory. Taking the approximate precision as a criterion, algorithm 2 chooses the sample space with a good representative. Hence, the clustering sample set in inducing and computing optimal dividing matrix can be achieved. Several theorems are proposed to provide strict theoretic foundations for the execution of the algorithm model. An applied example based on the new algorithm model is given, whose result verifies the feasibility of this new algorithm model.展开更多
In the study,the reasonable sampling of the grey Aneurolepidium chinense of green grassland,the grey-green A.chinense of green grassland,the grey A.chinense of Wulimu and the grey-green A.chinense of Wulimu were analy...In the study,the reasonable sampling of the grey Aneurolepidium chinense of green grassland,the grey-green A.chinense of green grassland,the grey A.chinense of Wulimu and the grey-green A.chinense of Wulimu were analyzed by ISSR.Eight primers with clear and diverse products were screened out from 20 primers and 47 DNA fragments were amplified from 39 individuals.The average number of DNA fragments produced by each primer was 5.9,and polymorphic bands were 41 and the polymorphic rate was 87.23%,which could r...展开更多
Background As the most widely cultivated fiber crop,cotton production depends on hybridization to unlock the yield potential of current varieties.A deep understanding of genetic dissection is crucial for the cultivati...Background As the most widely cultivated fiber crop,cotton production depends on hybridization to unlock the yield potential of current varieties.A deep understanding of genetic dissection is crucial for the cultivation of enhanced hybrid plants with desired traits,such as high yield and fine fiber quality.In this study,the general combining ability(GCA)and specific combining ability(SCA)of yield and fiber quality of nine cotton parents(six lines and three testers)and eighteen F1 crosses produced using a line×tester mating design were analyzed.Results The results revealed significant effects of genotypes,parents,crosses,and interactions between parents and crosses for most of the studied traits.Moreover,the effects of both additive and non-additive gene actions played a notably significant role in the inheritance of most of the yield and fiber quality attributes.The F1 hybrids of(Giza 90×Aust)×Giza 86,Uzbekistan 1×Giza 97,and Giza 96×Giza 97 demonstrated superior performance due to their favorable integration of high yield attributes and premium fiber quality characteristics.Path analysis revealed that lint yield has the highest positive direct effect on seed cotton yield,while lint percentage showed the highest negative direct effect on seed cotton yield.Principal component analysis identified specific parents and hybrids associated with higher cotton yield,fiber quality,and other agronomic traits.Conclusion This study provides insights into identifying potential single-and three-way cross hybrids with superior cotton yield and fiber quality characteristics,laying a foundation for future research on improving fiber quality in cotton.展开更多
Analytic hierarchy process(Group AHP) is combined with two different methods of assigning experts' priority to weight indicators in building energy efficiency assessment.One is to assign the experts' priority ...Analytic hierarchy process(Group AHP) is combined with two different methods of assigning experts' priority to weight indicators in building energy efficiency assessment.One is to assign the experts' priority averagely,and the other is to use cluster analysis to assign experts' priority.The results show that,1) Different expert's priority assigns result in great different weights of indicators in building energy efficiency assessment,therefore,the method of assigning experts' priority should be taken into account carefully while weighting indicators of building energy efficiency assessment using Group AHP;2) Three indicators are found to be overwhelmingly important in residential building energy efficiency assessment in the hot summer and cold winter zone in China.They are 'Outdoor & indoor shadow','Heating & air-conditioning facilities' and 'Insulation of envelope';3) The method combining cluster analysis with Group AHP to weight indicator of building energy efficiency assessment has the advantage of finding overwhelming important indicator,whereas,some less important indicators have a tendency to be ignored.A useful reference is provided for building energy conservation including policy revision and energy efficient residential building design.展开更多
In order to solve internal logistics problems of iron and steel works,such as low transportation efficiency of vehicles and high transportation cost,the production process and traditional transportation style of iron ...In order to solve internal logistics problems of iron and steel works,such as low transportation efficiency of vehicles and high transportation cost,the production process and traditional transportation style of iron and steel works were introduced.The internal transport tasks of iron and steel works were grouped based on cluster analysis according to demand time of the transportation.An improved vehicle scheduling model of semi-trailer swap transport among loading nodes and unloading nodes in one task group was set up.The algorithm was designed to solve the vehicle routing problem with simultaneous pick-up and delivery(VRPSPD) problem based on semi-trailer swap transport.A solving program was written by MATLAB software and the method to figure out the optimal path of each grouping was obtained.The dropping and pulling transportation plan of the tractor was designed.And an example of semi-trailer swap transport in iron and steel works was given.The results indicate that semi-trailer swap transport can decrease the numbers of vehicles and drivers by 54.5% and 88.6% respectively compared with decentralized scheduling in iron and steel works,and the total distance traveled reduces by 43.5%.The semi-trailer swap transport can help the iron and steel works develop the production in intension.展开更多
The contents of 34 kinds of flavor component in tobacco leaf were determinated with GC-MS/SIM after its being extracted by simultaneous distillation and extraction(SDE),then the different class tobacco leaf coming fro...The contents of 34 kinds of flavor component in tobacco leaf were determinated with GC-MS/SIM after its being extracted by simultaneous distillation and extraction(SDE),then the different class tobacco leaf coming from different area were clustered with cluster analysis under the independent variable of tobacco flavor contents.展开更多
Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality dat...Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality data sets of the Second Songhua River(SSHR) basin in China,obtained during two years(2012-2013) of monitoring of 10 physicochemical parameters at 15 different sites.The results showed that most of physicochemical parameters varied significantly among the sampling sites.Three significant groups,highly polluted(HP),moderately polluted(MP) and less polluted(LP),of sampling sites were obtained through Hierarchical agglomerative CA on the basis of similarity of water quality characteristics.DA identified p H,F,DO,NH3-N,COD and VPhs were the most important parameters contributing to spatial variations of surface water quality.However,DA did not give a considerable data reduction(40% reduction).PCA/FA resulted in three,three and four latent factors explaining 70%,62% and 71% of the total variance in water quality data sets of HP,MP and LP regions,respectively.FA revealed that the SSHR water chemistry was strongly affected by anthropogenic activities(point sources:industrial effluents and wastewater treatment plants;non-point sources:domestic sewage,livestock operations and agricultural activities) and natural processes(seasonal effect,and natural inputs).PCA/FA in the whole basin showed the best results for data reduction because it used only two parameters(about 80% reduction) as the most important parameters to explain 72% of the data variation.Thus,this work illustrated the utility of multivariate statistical techniques for analysis and interpretation of datasets and,in water quality assessment,identification of pollution sources/factors and understanding spatial variations in water quality for effective stream water quality management.展开更多
Assessment of temporal and spatial variations in surface water quality is important to evaluate the health of a watershed and make necessary management decisions to control current and future pollution of receiving wa...Assessment of temporal and spatial variations in surface water quality is important to evaluate the health of a watershed and make necessary management decisions to control current and future pollution of receiving water bodies. In this work, surface water quality data for 12 physical and chemical parameters collected from 10 sampling sites in the Nenjiang River basin during the years(2012-2013) were analyzed. The results show that river water quality has significant temporal and spatial variations. Hierarchical cluster analysis(HCA) grouped 12 months into three periods(LF, MF and HF) and classified 10 monitoring sites into three regions(LP, MP and HP) based on the similarity of water quality characteristics. The principle component analysis(PCA)/factor analysis(FA) was used to recognize the factors or origins responsible for temporal and spatial water quality variations. Temporal and spatial PCA/FA revealed that the Nenjiang River water chemistry was strongly affected by rock/water interaction, hydrologic processes and anthropogenic activities. This work demonstrates that the application of HCA and PCA/FA has achieved meaningful classification based on temporal and spatial criteria.展开更多
Background:Salt stress significantly inhibits the growth,development,and productivity of cotton because of osmotic,ionic,and oxidative stresses.Therefore,the screening and development of salt tolerant cotton cultivars...Background:Salt stress significantly inhibits the growth,development,and productivity of cotton because of osmotic,ionic,and oxidative stresses.Therefore,the screening and development of salt tolerant cotton cultivars is a key issue towards sustainable agriculture.This study subjected 11 upland cotton genotypes at the seedling growth stage to five different salt concentrations and evaluated their salt tolerance and reliable traits.Results:Several morpho-physiological traits were measured after 10 days of salinity treatment and the salt tolerance performance varied significantly among the tested cotton genotypes.The optimal Na Cl concentration for the evaluation of salt tolerance was 200 mmol·L-1.Membership function value and salt tolerance index were used to identify the most consistent salt tolerance traits.Leaf relative water content and photosynthesis were identified as reliable indicators for salt tolerance at the seedling stage.All considered traits related to salt tolerance indices were significantly and positively correlated with each other except for malondialdehyde.Cluster heat map analysis based on the morpho-physiological salt tolerance-indices clearly discriminated the 11 cotton genotypes into three different salt tolerance clusters.Cluster I represented the salt-tolerant genotypes(Z9807,Z0228,and Z7526)whereas clusters II(Z0710,Z7514,Z1910,and Z7516)and III(Z0102,Z7780,Z9648,and Z9612)represented moderately salttolerant and salt-sensitive genotypes,respectively.Conclusions:A hydroponic screening system was established.Leaf relative water content and photosynthesis were identified as two reliable traits that adequately represented the salt tolerance of cotton genotypes at the seedling growth stage.Furthermore,three salt-tolerant genotypes were identified,which might be used as genetic resources for the salt-tolerance breeding of cotton.展开更多
Traditional DEA-based ranking techniques have some pitfalls such as ignoring the inherent differences among decision making units （DMUs）, or lacking a common weight-based ranking, etc. To overcome these obstacles, t...Traditional DEA-based ranking techniques have some pitfalls such as ignoring the inherent differences among decision making units （DMUs）, or lacking a common weight-based ranking, etc. To overcome these obstacles, the paper first examines the possible differences among all DMUs such as the technical efficiency difference, the preference structure difference and the within-group position difference. Based upon the above differences this paper induces an integrated ranking measurement which helps to give a fair and full ranking for all DMUs under evaluation. Following the three types of differences, this approach behaves greatly elaborately, accurately and reasonably. Finally, the results from the Olympics achievement evaluation approve the acceptability of this approach.展开更多
A total of 69 random primers were screened by using random amplified polymorphic DNA （RAPD） markers to analyze the genetic bands of 32 Kentucky bluegrass cultivars. A total of 197 bands were amplified from 46 primer...A total of 69 random primers were screened by using random amplified polymorphic DNA （RAPD） markers to analyze the genetic bands of 32 Kentucky bluegrass cultivars. A total of 197 bands were amplified from 46 primers, among which 195 bands were polymorphic. Each primer could amplify one to nine polymorphic bands with an average of 4.3 per primer. Based on similarity coefficient analysis of RAPD results and by using NTSYS software to cluster analyze with the average UPGMA method, the result showed that 18 cultivars of the 32 were in group 1, three cultivars were in group 2, two cultivars were in group 3, eight cultivars were in group 4, and only one cultivar in group 5.展开更多
文摘According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferences and the consistency of expert＇s collating vectors,but they lack of the measure of information similarity.So it may occur that although the collating vector is similar to the group consensus,information uncertainty is great of a certain expert.However,it is clustered to a larger group and given a high weight.For this,a new aggregation method based on entropy and cluster analysis in group decision-making process is provided,in which the collating vectors are classified with information similarity coefficient,and the experts＇ weights are determined according to the result of classification,the entropy of collating vectors and the judgment matrix consistency.Finally,a numerical example shows that the method is feasible and effective.
基金Supported by the Doctoral Fund of Northeast Agricultural University(2009RC41)Postdoctoral Grants of Heilongjiang Province(LBH-Z10265)
文摘For the first time, we used Tullgren method made a study on vertical migrating and cluster analysis of the soil mesofauna in Dongying Halophytes Garden in the Yellow River Delta （YRD）, Shandong Province. The results showed that the soil mesofauna tended to gather on soil surface in most samples at most times, but the vertical migrating greatly varied in different seasons or environment conditions. Acari was the dominant group. The index of diversity of the soil fauna was correlated with the index of evenness. The Acari＇s number of individuals infected other species and numbers. Dominant group-Aeari made greater contribution to the result of cluster analysis, and there were significant differences between communities in different habitats by cluster analysis with both Bray-Curtis and Jaccard similarity coefficient.
基金Supported by Platform Construction for Germplasm Resources of China Tobacco (2007, 152)
文摘Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the length to width, stem girth, dates of budding, leaf yield and ratio of the prime-medium tobacco. The leaf number and the central leaf length showed a positive or a strong positive correlation with the yield per plant. And the leaf number and leaf yield per plant showed a strong positive correlation with the ratio of prime-medium tobacco. The results showed that the leaf yield per plant among these characteristics played a major role in determining the ratio of prime-medium tobacco while the others were less related with the ratio. Square sum of deviation method cluster analyses showed that 24 pure lines of flue-cured tobacco were clustered into two groups. Of the pure lines, Line T1706 and Line T1245 had a far relationship with all other lines, and also had a heterosis when crossed with the other lines. Lines Guangdonghuang 1 and R72（3）B-2-1 were closely related.
文摘The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was needed. The relationship can be deduced by virtual of FEM (Finite Element Method ), ANN (Artificial Neural Network) or MRA (Multiple Regression Analysis). MR A is on the basis of a total understanding of the temperature distribution of th e machine tool. Although the more the temperatures measured are, the more accura te the MRA is, too more temperatures will hinder the analysis calculation. So it is necessary to identify the key temperatures of the machine tool. The selectio n of key temperatures decides the efficiency and precision of MRA. Because of th e complexities and multi-input and multi-output structure of the relationships , the exact quantitative portions as well as the unclear portions must be taken into consideration together to improve the identification of key temperatures. I n this paper, a fuzzy cluster analysis was used to select the key temperatures. The substance of identifying the key temperatures is to group all temperatures b y their relativity, and then to select a temperature from each group as the repr esentation. A fuzzy cluster analysis can uncover the relationships between t he thermal field and deformations more truly and thoroughly. A fuzzy cluster ana lysis is the cluster analysis based on fuzzy sets. Given U={u i|i=0,...,N}, in which u i is the temperature measured, a fuzzy matrix R can be obta ined. The transfer close package t(R) can be deduced from R. A fuzzy clu ster of U then conducts on the basis of t(R). Based on the fuzzy cluster analysis discussed above, this paper identified the k ey temperatures of a horizontal machining center. The number of the temperatures measured was reduced to 4 from 32, and then the multiple regression relationshi p models between the 4 temperatures and the thermal deformations of the spindle were drawn. The remnant errors between the regression models and measured deform ations reached a satisfying low level. At the same time, the decreasing of tempe rature variable number improved the efficiency of measure and analysis greatly.
基金Project(41272304)supported by the National Natural Science Foundation of ChinaProject(51074177)jointly supported by the National Natural Science Foundation and Shanghai Baosteel Group Corporation,ChinaProject(CX2012B070)supported by Hunan Provincial Innovation Fund for Postgraduated Students,China
文摘Based on structural surface normal vector spherical distance and the pole stereographic projection Euclidean distance,two distance functions were established.The cluster analysis of structure surface was conducted by the use of ATTA clustering methods based on ant colony piles,and Silhouette index was introduced to evaluate the clustering effect.The clustering analysis of the measured data of Sanshandao Gold Mine shows that ant colony ATTA-based clustering method does better than K-mean clustering analysis.Meanwhile,clustering results of ATTA method based on pole Euclidean distance and ATTA method based on normal vector spherical distance have a great consistence.The clustering results are most close to the pole isopycnic graph.It can efficiently realize grouping of structural plane and determination of the dominant structural surface direction.It is made up for the defects of subjectivity and inaccuracy in icon measurement approach and has great engineering value.
文摘This paper proposes a suppression method of the deceptive false target(FT) produced by digital radio frequency memory(DRFM) in a multistatic radar system. The simulated deceptive false targets from DRFM cannot be easily discriminated and suppressed with traditional radar systems. Therefore, multistatic radar has attracted considerable interest as it provides improved performance against deception jamming due to several separated receivers. This paper first investigates the received signal model in the presence of multiple false targets in all receivers of the multistatic radar. Then, obtain the propagation time delays of the false targets based on the cross-correlation test of the received signals in different receivers. In doing so, local-density-based spatial clustering of applications with noise(LDBSCAN) is proposed to discriminate the FTs from the physical targets(PTs) after compensating the FTs time delays, where the FTs are approximately coincident with one position, while PTs possess small dispersion.Numerical simulations are carried out to demonstrate the feasibility and validness of the proposed method.
文摘The fuzzy C-means clustering algorithm(FCM) to the fuzzy kernel C-means clustering algorithm(FKCM) to effectively perform cluster analysis on the diversiform structures are extended, such as non-hyperspherical data, data with noise, data with mixture of heterogeneous cluster prototypes, asymmetric data, etc. Based on the Mercer kernel, FKCM clustering algorithm is derived from FCM algorithm united with kernel method. The results of experiments with the synthetic and real data show that the FKCM clustering algorithm is universality and can effectively unsupervised analyze datasets with variform structures in contrast to FCM algorithm. It is can be imagined that kernel-based clustering algorithm is one of important research direction of fuzzy clustering analysis.
文摘In this study, we used RAPD to analyze four kinds of color-flowered Salvia splendens Ker-Gawl, and the optimal RAPD reaction conditions were the optimal reaction mixture （25 μL total volume） that contained 2.0 μL 10×buffer, 0.45 mmol·L^-1 dNTPs, 2.0 mmol· L^-1 Mg^2＋, 2 U Taq DNA polymerase, 0.30 umol·L^-2 primer and 40 ng genomic DNA. Total 84 bands were amplified from 12 primers used, and the differential bands had 28 bands, which was 33% of total bands. In cluster group analysis, the four kinds of color-flowered were divided into two styles. One style is that the red color and red-white color were grouped together, then they grouped with purple color into one cluster, and the white color was another style.
文摘To investigate the judging problem of optimal dividing matrix among several fuzzy dividing matrices in fuzzy dividing space, correspondingly, which is determined by the various choices of cluster samples in the totality sample space, two algorithms are proposed on the basis of the data analysis method in rough sets theory： information system discrete algorithm （algorithm 1） and samples representatives judging algorithm （algorithm 2）. On the principle of the farthest distance, algorithm 1 transforms continuous data into discrete form which could be transacted by rough sets theory. Taking the approximate precision as a criterion, algorithm 2 chooses the sample space with a good representative. Hence, the clustering sample set in inducing and computing optimal dividing matrix can be achieved. Several theorems are proposed to provide strict theoretic foundations for the execution of the algorithm model. An applied example based on the new algorithm model is given, whose result verifies the feasibility of this new algorithm model.
文摘In the study,the reasonable sampling of the grey Aneurolepidium chinense of green grassland,the grey-green A.chinense of green grassland,the grey A.chinense of Wulimu and the grey-green A.chinense of Wulimu were analyzed by ISSR.Eight primers with clear and diverse products were screened out from 20 primers and 47 DNA fragments were amplified from 39 individuals.The average number of DNA fragments produced by each primer was 5.9,and polymorphic bands were 41 and the polymorphic rate was 87.23%,which could r...
文摘Background As the most widely cultivated fiber crop,cotton production depends on hybridization to unlock the yield potential of current varieties.A deep understanding of genetic dissection is crucial for the cultivation of enhanced hybrid plants with desired traits,such as high yield and fine fiber quality.In this study,the general combining ability(GCA)and specific combining ability(SCA)of yield and fiber quality of nine cotton parents(six lines and three testers)and eighteen F1 crosses produced using a line×tester mating design were analyzed.Results The results revealed significant effects of genotypes,parents,crosses,and interactions between parents and crosses for most of the studied traits.Moreover,the effects of both additive and non-additive gene actions played a notably significant role in the inheritance of most of the yield and fiber quality attributes.The F1 hybrids of(Giza 90×Aust)×Giza 86,Uzbekistan 1×Giza 97,and Giza 96×Giza 97 demonstrated superior performance due to their favorable integration of high yield attributes and premium fiber quality characteristics.Path analysis revealed that lint yield has the highest positive direct effect on seed cotton yield,while lint percentage showed the highest negative direct effect on seed cotton yield.Principal component analysis identified specific parents and hybrids associated with higher cotton yield,fiber quality,and other agronomic traits.Conclusion This study provides insights into identifying potential single-and three-way cross hybrids with superior cotton yield and fiber quality characteristics,laying a foundation for future research on improving fiber quality in cotton.
基金Project(2010R10036) supported by the Science and Technology Department of Zhejiang Province, China
文摘Analytic hierarchy process(Group AHP) is combined with two different methods of assigning experts' priority to weight indicators in building energy efficiency assessment.One is to assign the experts' priority averagely,and the other is to use cluster analysis to assign experts' priority.The results show that,1) Different expert's priority assigns result in great different weights of indicators in building energy efficiency assessment,therefore,the method of assigning experts' priority should be taken into account carefully while weighting indicators of building energy efficiency assessment using Group AHP;2) Three indicators are found to be overwhelmingly important in residential building energy efficiency assessment in the hot summer and cold winter zone in China.They are 'Outdoor & indoor shadow','Heating & air-conditioning facilities' and 'Insulation of envelope';3) The method combining cluster analysis with Group AHP to weight indicator of building energy efficiency assessment has the advantage of finding overwhelming important indicator,whereas,some less important indicators have a tendency to be ignored.A useful reference is provided for building energy conservation including policy revision and energy efficient residential building design.
基金Project(70671108) supported by the National Natural Science Foundation of China
文摘In order to solve internal logistics problems of iron and steel works,such as low transportation efficiency of vehicles and high transportation cost,the production process and traditional transportation style of iron and steel works were introduced.The internal transport tasks of iron and steel works were grouped based on cluster analysis according to demand time of the transportation.An improved vehicle scheduling model of semi-trailer swap transport among loading nodes and unloading nodes in one task group was set up.The algorithm was designed to solve the vehicle routing problem with simultaneous pick-up and delivery(VRPSPD) problem based on semi-trailer swap transport.A solving program was written by MATLAB software and the method to figure out the optimal path of each grouping was obtained.The dropping and pulling transportation plan of the tractor was designed.And an example of semi-trailer swap transport in iron and steel works was given.The results indicate that semi-trailer swap transport can decrease the numbers of vehicles and drivers by 54.5% and 88.6% respectively compared with decentralized scheduling in iron and steel works,and the total distance traveled reduces by 43.5%.The semi-trailer swap transport can help the iron and steel works develop the production in intension.
文摘The contents of 34 kinds of flavor component in tobacco leaf were determinated with GC-MS/SIM after its being extracted by simultaneous distillation and extraction(SDE),then the different class tobacco leaf coming from different area were clustered with cluster analysis under the independent variable of tobacco flavor contents.
基金Project (2012ZX07501002-001) supported by the Ministry of Science and Technology of China
文摘Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality data sets of the Second Songhua River(SSHR) basin in China,obtained during two years(2012-2013) of monitoring of 10 physicochemical parameters at 15 different sites.The results showed that most of physicochemical parameters varied significantly among the sampling sites.Three significant groups,highly polluted(HP),moderately polluted(MP) and less polluted(LP),of sampling sites were obtained through Hierarchical agglomerative CA on the basis of similarity of water quality characteristics.DA identified p H,F,DO,NH3-N,COD and VPhs were the most important parameters contributing to spatial variations of surface water quality.However,DA did not give a considerable data reduction(40% reduction).PCA/FA resulted in three,three and four latent factors explaining 70%,62% and 71% of the total variance in water quality data sets of HP,MP and LP regions,respectively.FA revealed that the SSHR water chemistry was strongly affected by anthropogenic activities(point sources:industrial effluents and wastewater treatment plants;non-point sources:domestic sewage,livestock operations and agricultural activities) and natural processes(seasonal effect,and natural inputs).PCA/FA in the whole basin showed the best results for data reduction because it used only two parameters(about 80% reduction) as the most important parameters to explain 72% of the data variation.Thus,this work illustrated the utility of multivariate statistical techniques for analysis and interpretation of datasets and,in water quality assessment,identification of pollution sources/factors and understanding spatial variations in water quality for effective stream water quality management.
基金Project(2012ZX07501002-001)supported by Major Science and Technology Program for Water Pollution Control and Treatment of the Ministry of Science and Technology,China
文摘Assessment of temporal and spatial variations in surface water quality is important to evaluate the health of a watershed and make necessary management decisions to control current and future pollution of receiving water bodies. In this work, surface water quality data for 12 physical and chemical parameters collected from 10 sampling sites in the Nenjiang River basin during the years(2012-2013) were analyzed. The results show that river water quality has significant temporal and spatial variations. Hierarchical cluster analysis(HCA) grouped 12 months into three periods(LF, MF and HF) and classified 10 monitoring sites into three regions(LP, MP and HP) based on the similarity of water quality characteristics. The principle component analysis(PCA)/factor analysis(FA) was used to recognize the factors or origins responsible for temporal and spatial water quality variations. Temporal and spatial PCA/FA revealed that the Nenjiang River water chemistry was strongly affected by rock/water interaction, hydrologic processes and anthropogenic activities. This work demonstrates that the application of HCA and PCA/FA has achieved meaningful classification based on temporal and spatial criteria.
基金supported by National Key R&D Program(2017YFD0101600)State Key Laboratory of Cotton Biology(CB2019C17)。
文摘Background:Salt stress significantly inhibits the growth,development,and productivity of cotton because of osmotic,ionic,and oxidative stresses.Therefore,the screening and development of salt tolerant cotton cultivars is a key issue towards sustainable agriculture.This study subjected 11 upland cotton genotypes at the seedling growth stage to five different salt concentrations and evaluated their salt tolerance and reliable traits.Results:Several morpho-physiological traits were measured after 10 days of salinity treatment and the salt tolerance performance varied significantly among the tested cotton genotypes.The optimal Na Cl concentration for the evaluation of salt tolerance was 200 mmol·L-1.Membership function value and salt tolerance index were used to identify the most consistent salt tolerance traits.Leaf relative water content and photosynthesis were identified as reliable indicators for salt tolerance at the seedling stage.All considered traits related to salt tolerance indices were significantly and positively correlated with each other except for malondialdehyde.Cluster heat map analysis based on the morpho-physiological salt tolerance-indices clearly discriminated the 11 cotton genotypes into three different salt tolerance clusters.Cluster I represented the salt-tolerant genotypes(Z9807,Z0228,and Z7526)whereas clusters II(Z0710,Z7514,Z1910,and Z7516)and III(Z0102,Z7780,Z9648,and Z9612)represented moderately salttolerant and salt-sensitive genotypes,respectively.Conclusions:A hydroponic screening system was established.Leaf relative water content and photosynthesis were identified as two reliable traits that adequately represented the salt tolerance of cotton genotypes at the seedling growth stage.Furthermore,three salt-tolerant genotypes were identified,which might be used as genetic resources for the salt-tolerance breeding of cotton.
基金supported partly by the National Natural Science Fundation of China for Innovative Research Groups(T0821001)the National Natural Science Fundation of China(70801056)University of Science and Technology of China Science Funds for Young Scholars.
文摘Traditional DEA-based ranking techniques have some pitfalls such as ignoring the inherent differences among decision making units （DMUs）, or lacking a common weight-based ranking, etc. To overcome these obstacles, the paper first examines the possible differences among all DMUs such as the technical efficiency difference, the preference structure difference and the within-group position difference. Based upon the above differences this paper induces an integrated ranking measurement which helps to give a fair and full ranking for all DMUs under evaluation. Following the three types of differences, this approach behaves greatly elaborately, accurately and reasonably. Finally, the results from the Olympics achievement evaluation approve the acceptability of this approach.
基金Supported by the National Natural Science Foundation of China (30871735 31272191)+2 种基金the National Key Technology R&D Program(2006BAD01A19-4-2)the Natural Science Foundation of Heilongjiang Province (C0207 C200619)
文摘A total of 69 random primers were screened by using random amplified polymorphic DNA （RAPD） markers to analyze the genetic bands of 32 Kentucky bluegrass cultivars. A total of 197 bands were amplified from 46 primers, among which 195 bands were polymorphic. Each primer could amplify one to nine polymorphic bands with an average of 4.3 per primer. Based on similarity coefficient analysis of RAPD results and by using NTSYS software to cluster analyze with the average UPGMA method, the result showed that 18 cultivars of the 32 were in group 1, three cultivars were in group 2, two cultivars were in group 3, eight cultivars were in group 4, and only one cultivar in group 5.
