Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
To ascertain the genetic diversity of gray leaf spot pathogen on Dictamnus dasycarpus popoulation in Heilongjiang Province,a total of 57 strains of Paracercospora dictamnicola were isolated and purified from the disea...To ascertain the genetic diversity of gray leaf spot pathogen on Dictamnus dasycarpus popoulation in Heilongjiang Province,a total of 57 strains of Paracercospora dictamnicola were isolated and purified from the diseased samples collected from five Chinese herbal medicine planting areas in Heilongjiang Province between the years of 2021 and 2022.Repetitive extragenic palindromic polymerase chain reaction(Rep–PCR)was used to amplify 57 isolates of gray leaf spot pathogen on D.dasycarpus from different regions of Heilongjiang Province.The polymorphic bands amplified by three sets of primers accounted for more than 80%.Cluster analysis results showed that at a similarity coefficient of 0.67,the gray leaf spot pathogen on D.dasycarpus in Heilongjiang Province could be divided into five major genetic groups.Genetic diversity parameter analysis indicated that there were certain differences in genetic richness among the geographic populations of gray leaf spot pathogen on D.dasycarpus from different regions.Analysis of molecular variance(AMOVA)revealed that genetic variation among strains mainly originated within populations.The genetic differentiation and relationships of gray leaf spot pathogen on D.dasycarpus from different geographic regions of Heilongjiang Province indicated that genetic differentiation and kinship among populations were somewhat related to their geographic distance.The greater the geographic distance,the higher the genetic differentiation coefficient,and the lower the genetic uniformity among populations.展开更多
Coronavirus is an RNA virus that can infect both humans and animals,posing a significant threat to agriculture and public health.Although coronaviruses are highly host-specific,their ability to infect multiple hosts,c...Coronavirus is an RNA virus that can infect both humans and animals,posing a significant threat to agriculture and public health.Although coronaviruses are highly host-specific,their ability to infect multiple hosts,combined with the structure of their genome,gives them a high probability of genetic recombination and mutation,leading to the creation of novel viruses.In recent years,with the establishment and development of reverse genetic manipulation techniques,substantial technical support has been provided for studying the structure and function of the coronavirus genome,the development of novel vaccines and drugs and the construction of viral expression vectors.This paper briefly described the progress in research on coronaviruses and their reverse genetic system construction strategies,aiming to provide some references for future coronavirus research.展开更多
With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a c...With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a convenient and visual technique with low equipment requirements and high sensitivity for the field detection of GM plants is still lacking.On the basis of the existing recombinase polymerase amplification(RPA)technique,we developed a multiplex RPA(multi-RPA)method that can simultaneously detect three transgenic elements,including the cauliflower mosaic virus 35S gene(CaMV35S)promoter,neomycin phosphotransferaseⅡgene(NptⅡ)and hygromycin B phosphotransferase gene(Hyg),thus improving the detection rate.Moreover,we coupled this multi-RPA technique with the CRISPR/Cas12a reporter system,which enabled the detection results to be clearly observed by naked eyes under ultraviolet(UV)light(254 nm;which could be achieved by a portable UV flashlight),therefore establishing a multi-RPA visual detection technique.Compared with the traditional test strip detection method,this multi-RPA-CRISPR/Cas12a technique has the higher specificity,higher sensitivity,wider application range and lower cost.Compared with other polymerase chain reaction(PCR)techniques,it also has the advantages of low equipment requirements and visualization,making it a potentially feasible method for the field detection of GM plants.展开更多
Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and ...Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and development of the army need top-down,top-level design,and comprehensive plan-ning.The traditional project development model is no longer suf-ficient to meet the army’s complex capability requirements.Projects in various fields need to be developed and coordinated to form a joint force and improve the army’s combat effective-ness.At the same time,when a program consists of large-scale project data,the effectiveness of the traditional,precise mathe-matical planning method is greatly reduced because it is time-consuming,costly,and impractical.To solve above problems,this paper proposes a multi-stage program optimization model based on a heterogeneous network and hybrid genetic algo-rithm and verifies the effectiveness and feasibility of the model and algorithm through an example.The results show that the hybrid algorithm proposed in this paper is better than the exist-ing meta-heuristic algorithm.展开更多
The learning algorithms of causal discovery mainly include score-based methods and genetic algorithms(GA).The score-based algorithms are prone to searching space explosion.Classical GA is slow to converge,and prone to...The learning algorithms of causal discovery mainly include score-based methods and genetic algorithms(GA).The score-based algorithms are prone to searching space explosion.Classical GA is slow to converge,and prone to falling into local optima.To address these issues,an improved GA with domain knowledge(IGADK)is proposed.Firstly,domain knowledge is incorporated into the learning process of causality to construct a new fitness function.Secondly,a dynamical mutation operator is introduced in the algorithm to accelerate the convergence rate.Finally,an experiment is conducted on simulation data,which compares the classical GA with IGADK with domain knowledge of varying accuracy.The IGADK can greatly reduce the number of iterations,populations,and samples required for learning,which illustrates the efficiency and effectiveness of the proposed algorithm.展开更多
Thinning of antenna arrays has been a popular topic for the last several decades.With increasing computational power,this optimization task acquired a new hue.This paper suggests a genetic algorithm as an instrument f...Thinning of antenna arrays has been a popular topic for the last several decades.With increasing computational power,this optimization task acquired a new hue.This paper suggests a genetic algorithm as an instrument for antenna array thinning.The algorithm with a deliberately chosen fitness function allows synthesizing thinned linear antenna arrays with low peak sidelobe level(SLL)while maintaining the half-power beamwidth(HPBW)of a full linear antenna array.Based on results from existing papers in the field and known approaches to antenna array thinning,a classification of thinning types is introduced.The optimal thinning type for a linear thinned antenna array is determined on the basis of a maximum attainable SLL.The effect of thinning coefficient on main directional pattern characteristics,such as peak SLL and HPBW,is discussed for a number of amplitude distributions.展开更多
Agile earth observation satellites(AEOSs)represent a new generation of satellites with three degrees of freedom(pitch,roll,and yaw);they possess a long visible time window(VTW)for ground targets and support imaging at...Agile earth observation satellites(AEOSs)represent a new generation of satellites with three degrees of freedom(pitch,roll,and yaw);they possess a long visible time window(VTW)for ground targets and support imaging at any moment within the VTW.However,different observation times demonstrate different cloud cover distributions,which exhibit different effects on the AEOS observation.Previous studies ignored pitch angles,discretized VTWs,or fixed cloud cover for every VTW,which led to the loss of intermediate observation states,thus these studies are not suitable for AEOS scheduling considering cloud cover distribution.In this study,a relationship formula between the cloud cover and observation time is proposed to calculate the cloud cover for every observation time,and a relationship formula between the observation time and pitch angle is designed to calculate the pitch angle for every observation time in the VTW.A refined model including the pitch angle,roll angle,and cloud cover distribution is established,which can make the scheme closer to the actual application of AEOSs.A hybrid genetic simulated annealing(HGSA)algorithm for AEOS scheduling is proposed,which integrates the advantages of genetic and simulated annealing algorithms and can effectively avoid falling into a local optimal solution.The experiments are conducted to compare the proposed algorithm with the traditional algorithms,the results verify that the proposed model and algorithm are efficient and effective for AEOS scheduling considering cloud cover distribution.展开更多
2025年3月17日,国际顶级学术期刊《自然·遗传学》(Nature Genetics)刊发题为“Genomic analysis of 1325 Camellia accessions sheds light on agronomic and metabolic traits for tea plant improvement”的研究性论文。该研究...2025年3月17日,国际顶级学术期刊《自然·遗传学》(Nature Genetics)刊发题为“Genomic analysis of 1325 Camellia accessions sheds light on agronomic and metabolic traits for tea plant improvement”的研究性论文。该研究由福建省农业科学院茶叶研究所与中国农业科学院农业基因组研究所等多家单位合作完成。本研究通过对茶树及其近缘种的基因组进行深度重测序,构建了全面的茶树基因组遗传变异图谱,进而揭示了茶树的遗传多样性及其驯化状态。其结果为茶树的遗传进化和精准设计育种提供了有益见解以及重要参考资料。展开更多
By combing the properties of chaos optimization method and genetic algorithm,an adaptive mutative scale chaos genetic algorithm(AMSCGA) was proposed by using one-dimensional iterative chaotic self-map with infinite co...By combing the properties of chaos optimization method and genetic algorithm,an adaptive mutative scale chaos genetic algorithm(AMSCGA) was proposed by using one-dimensional iterative chaotic self-map with infinite collapses within the finite region of [-1,1].Some measures in the optimization algorithm,such as adjusting the searching space of optimized variables continuously by using adaptive mutative scale method and making the most circle time as its control guideline,were taken to ensure its speediness and veracity in seeking the optimization process.The calculation examples about three testing functions reveal that AMSCGA has both high searching speed and high precision.Furthermore,the average truncated generations,the distribution entropy of truncated generations and the ratio of average inertia generations were used to evaluate the optimization efficiency of AMSCGA quantificationally.It is shown that the optimization efficiency of AMSCGA is higher than that of genetic algorithm.展开更多
Background:Cotton is known for fiber extraction and it is grown in tropical and sub-tropical areas of the world due to having hot weather.Cotton crop has a significant role in GDP of Pakistan.Therefore,the two-years r...Background:Cotton is known for fiber extraction and it is grown in tropical and sub-tropical areas of the world due to having hot weather.Cotton crop has a significant role in GDP of Pakistan.Therefore,the two-years research was conducted to estimate heritability and association among various yield contributing parameters of cotton,i.e.,plant height,number of bolls per plant,number of sympodial branches per plant,seed cotton yield,boll weight,seed index,ginning outturn(GOT),fiber length,fiber strength,and fiber fineness.Results:Association analysis revealed that seed cotton yield had a significant positive correlation with plant height,number of bolls per plant,number of sympodial branches per plant,GOT,staple length and fiber strength.Staple length and fiber strength were negatively linked with each other.Estimates of heritability were high for all of the traits except the number of sympodial branches per plant and boll weight.Conclusion:The parent IUB-222 was found to be the best for plant height,the number of bolls per plant,boll weight,GOT,seed cotton yield,and seed index.The genotypes namely,NIAB-414 and VH-367 were identified as the best parents for fiber length,strength,and fineness.Among the crosses NIAB-414×IUB-222 was the best for the number of bolls per plant,seed index,seed cotton yield and fiber fineness,whereas,the cross of NIAB-414×CIM-632 was good for plant height.The combination of A555×CIM-632 was the best for the number of sympodial branches per plant,boll weight,fiber length,and strength,and VH-367×CIM-632 proved the best for GOT.展开更多
Background: Gossypium arboreum is a diploid species cultivated in the Old World. It possesses favorable characters that are valuable for developing superior cotton cultivars.Method: A set of 197 Gossypium arboreum acc...Background: Gossypium arboreum is a diploid species cultivated in the Old World. It possesses favorable characters that are valuable for developing superior cotton cultivars.Method: A set of 197 Gossypium arboreum accessions were genotyped using 80 genome-wide SSR markers to establish patterns of the genetic diversity and population structure. These accessions were collected from three major G. arboreum growing areas in China. A total of 255 alleles across 80 markers were identified in the genetic diversity analysis.Results: Three subgroups were found using the population structure analysis, corresponding to the Yangtze River Valley, North China, and Southwest China zones of G.arboreum growing areas in China. Average genetic distance and Polymorphic information content value of G. arboreum population were 0.34 and 0.47, respectively, indicating high genetic diversity in the G. arboreum germplasm pool. The Phylogenetic analysis results concurred with the subgroups identified by Structure analysis with a few exceptions. Variations among and within three groups were observed to be 13.61% and 86.39%, respectively.Conclusion: The information regarding genetic diversity and population structure from this study is useful for genetic and genomic analysis and systematic utilization of economically important traits in G. arboreum.展开更多
Short sequence repeats(microsatellite,SSR)and expressed sequence tags-SSR(EST-SSR)markers were employed to analyze the genetic diversity of natural colored cotton varieties.AboutShort sequence repeats(microsatellite,S...Short sequence repeats(microsatellite,SSR)and expressed sequence tags-SSR(EST-SSR)markers were employed to analyze the genetic diversity of natural colored cotton varieties.AboutShort sequence repeats(microsatellite,SSR)and expressed sequence tags-SSR(EST-SSR)marker s were employed to analyze the genetic diversity of natural colored cotton varieties.About 490 pairs of SSR markers spanning the 26 chro mosomes were selected from the cotton micro satellite data-base,they were composed of the NAU,BNL,MUSS,and CIR markers,and there was one marker every 5 cM on average.展开更多
RAPD was used to study the genetic divergency and phylogenetic relationships of five breeds of domestic pigs,including Min pig,Duroc,Yorkshired,Landrace and Junmu I pig.We selected fourteen primers from eighty random ...RAPD was used to study the genetic divergency and phylogenetic relationships of five breeds of domestic pigs,including Min pig,Duroc,Yorkshired,Landrace and Junmu I pig.We selected fourteen primers from eighty random primers,caculated genetic distance index matrix and constructed phylogenetic tree with UPGMA methods.Genetic distance index matrix indicated that the genetic relationship between Junmu I pig and Landrace was the closest and the farthest between Duroc and min pig.展开更多
This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different he...This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.展开更多
A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced eff...A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar perfofmance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.展开更多
As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of c...As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of closed-loop supply chain was selected as fitness function, and a unique and tidy coding mode was adopted in the proposed algorithm. Then, some mutation and crossover operators were introduced to achieve discrete optimization of RCSCN structure. The simulation results show that the proposed algorithm can gain global optimal solution with good convergent performance and rapidity. The computing speed is only 22.16 s, which is shorter than those of the other optimization algorithms.展开更多
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
基金Supported by the Green Plant Protection Project of Heilongjiang Province(2130108)Key R&D Program Project of Heilongjiang Province(2023ZX02B0502)Heilongjiang Province Rice Modern Agriculture Industry Technology Collaborative Innovation System Project(2025)。
文摘To ascertain the genetic diversity of gray leaf spot pathogen on Dictamnus dasycarpus popoulation in Heilongjiang Province,a total of 57 strains of Paracercospora dictamnicola were isolated and purified from the diseased samples collected from five Chinese herbal medicine planting areas in Heilongjiang Province between the years of 2021 and 2022.Repetitive extragenic palindromic polymerase chain reaction(Rep–PCR)was used to amplify 57 isolates of gray leaf spot pathogen on D.dasycarpus from different regions of Heilongjiang Province.The polymorphic bands amplified by three sets of primers accounted for more than 80%.Cluster analysis results showed that at a similarity coefficient of 0.67,the gray leaf spot pathogen on D.dasycarpus in Heilongjiang Province could be divided into five major genetic groups.Genetic diversity parameter analysis indicated that there were certain differences in genetic richness among the geographic populations of gray leaf spot pathogen on D.dasycarpus from different regions.Analysis of molecular variance(AMOVA)revealed that genetic variation among strains mainly originated within populations.The genetic differentiation and relationships of gray leaf spot pathogen on D.dasycarpus from different geographic regions of Heilongjiang Province indicated that genetic differentiation and kinship among populations were somewhat related to their geographic distance.The greater the geographic distance,the higher the genetic differentiation coefficient,and the lower the genetic uniformity among populations.
基金Supported by the National Natural Science Foundation of China Joint Foundation Programme(U22A20527)。
文摘Coronavirus is an RNA virus that can infect both humans and animals,posing a significant threat to agriculture and public health.Although coronaviruses are highly host-specific,their ability to infect multiple hosts,combined with the structure of their genome,gives them a high probability of genetic recombination and mutation,leading to the creation of novel viruses.In recent years,with the establishment and development of reverse genetic manipulation techniques,substantial technical support has been provided for studying the structure and function of the coronavirus genome,the development of novel vaccines and drugs and the construction of viral expression vectors.This paper briefly described the progress in research on coronaviruses and their reverse genetic system construction strategies,aiming to provide some references for future coronavirus research.
基金the Experimental Technology Research Project of Zhejiang University(SYB202138)National Natural Science Foundation of China(32000195)。
文摘With the approval of more and more genetically modified(GM)crops in our country,GM safety management has become more important.Transgenic detection is a major approach for transgenic safety management.Nevertheless,a convenient and visual technique with low equipment requirements and high sensitivity for the field detection of GM plants is still lacking.On the basis of the existing recombinase polymerase amplification(RPA)technique,we developed a multiplex RPA(multi-RPA)method that can simultaneously detect three transgenic elements,including the cauliflower mosaic virus 35S gene(CaMV35S)promoter,neomycin phosphotransferaseⅡgene(NptⅡ)and hygromycin B phosphotransferase gene(Hyg),thus improving the detection rate.Moreover,we coupled this multi-RPA technique with the CRISPR/Cas12a reporter system,which enabled the detection results to be clearly observed by naked eyes under ultraviolet(UV)light(254 nm;which could be achieved by a portable UV flashlight),therefore establishing a multi-RPA visual detection technique.Compared with the traditional test strip detection method,this multi-RPA-CRISPR/Cas12a technique has the higher specificity,higher sensitivity,wider application range and lower cost.Compared with other polymerase chain reaction(PCR)techniques,it also has the advantages of low equipment requirements and visualization,making it a potentially feasible method for the field detection of GM plants.
基金supported by the National Natural Science Foundation of China(724701189072431011).
文摘Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and development of the army need top-down,top-level design,and comprehensive plan-ning.The traditional project development model is no longer suf-ficient to meet the army’s complex capability requirements.Projects in various fields need to be developed and coordinated to form a joint force and improve the army’s combat effective-ness.At the same time,when a program consists of large-scale project data,the effectiveness of the traditional,precise mathe-matical planning method is greatly reduced because it is time-consuming,costly,and impractical.To solve above problems,this paper proposes a multi-stage program optimization model based on a heterogeneous network and hybrid genetic algo-rithm and verifies the effectiveness and feasibility of the model and algorithm through an example.The results show that the hybrid algorithm proposed in this paper is better than the exist-ing meta-heuristic algorithm.
基金supported by the National Social Science Fund of China(2022-SKJJ-B-084).
文摘The learning algorithms of causal discovery mainly include score-based methods and genetic algorithms(GA).The score-based algorithms are prone to searching space explosion.Classical GA is slow to converge,and prone to falling into local optima.To address these issues,an improved GA with domain knowledge(IGADK)is proposed.Firstly,domain knowledge is incorporated into the learning process of causality to construct a new fitness function.Secondly,a dynamical mutation operator is introduced in the algorithm to accelerate the convergence rate.Finally,an experiment is conducted on simulation data,which compares the classical GA with IGADK with domain knowledge of varying accuracy.The IGADK can greatly reduce the number of iterations,populations,and samples required for learning,which illustrates the efficiency and effectiveness of the proposed algorithm.
文摘Thinning of antenna arrays has been a popular topic for the last several decades.With increasing computational power,this optimization task acquired a new hue.This paper suggests a genetic algorithm as an instrument for antenna array thinning.The algorithm with a deliberately chosen fitness function allows synthesizing thinned linear antenna arrays with low peak sidelobe level(SLL)while maintaining the half-power beamwidth(HPBW)of a full linear antenna array.Based on results from existing papers in the field and known approaches to antenna array thinning,a classification of thinning types is introduced.The optimal thinning type for a linear thinned antenna array is determined on the basis of a maximum attainable SLL.The effect of thinning coefficient on main directional pattern characteristics,such as peak SLL and HPBW,is discussed for a number of amplitude distributions.
基金supported by the National Natural Science Foundation of China(72071064,72271074,72001004)the Anhui Provincial Natural Science Foundation(2408085QG221).
文摘Agile earth observation satellites(AEOSs)represent a new generation of satellites with three degrees of freedom(pitch,roll,and yaw);they possess a long visible time window(VTW)for ground targets and support imaging at any moment within the VTW.However,different observation times demonstrate different cloud cover distributions,which exhibit different effects on the AEOS observation.Previous studies ignored pitch angles,discretized VTWs,or fixed cloud cover for every VTW,which led to the loss of intermediate observation states,thus these studies are not suitable for AEOS scheduling considering cloud cover distribution.In this study,a relationship formula between the cloud cover and observation time is proposed to calculate the cloud cover for every observation time,and a relationship formula between the observation time and pitch angle is designed to calculate the pitch angle for every observation time in the VTW.A refined model including the pitch angle,roll angle,and cloud cover distribution is established,which can make the scheme closer to the actual application of AEOSs.A hybrid genetic simulated annealing(HGSA)algorithm for AEOS scheduling is proposed,which integrates the advantages of genetic and simulated annealing algorithms and can effectively avoid falling into a local optimal solution.The experiments are conducted to compare the proposed algorithm with the traditional algorithms,the results verify that the proposed model and algorithm are efficient and effective for AEOS scheduling considering cloud cover distribution.
文摘2025年3月17日,国际顶级学术期刊《自然·遗传学》(Nature Genetics)刊发题为“Genomic analysis of 1325 Camellia accessions sheds light on agronomic and metabolic traits for tea plant improvement”的研究性论文。该研究由福建省农业科学院茶叶研究所与中国农业科学院农业基因组研究所等多家单位合作完成。本研究通过对茶树及其近缘种的基因组进行深度重测序,构建了全面的茶树基因组遗传变异图谱,进而揭示了茶树的遗传多样性及其驯化状态。其结果为茶树的遗传进化和精准设计育种提供了有益见解以及重要参考资料。
基金Project(60874114) supported by the National Natural Science Foundation of China
文摘By combing the properties of chaos optimization method and genetic algorithm,an adaptive mutative scale chaos genetic algorithm(AMSCGA) was proposed by using one-dimensional iterative chaotic self-map with infinite collapses within the finite region of [-1,1].Some measures in the optimization algorithm,such as adjusting the searching space of optimized variables continuously by using adaptive mutative scale method and making the most circle time as its control guideline,were taken to ensure its speediness and veracity in seeking the optimization process.The calculation examples about three testing functions reveal that AMSCGA has both high searching speed and high precision.Furthermore,the average truncated generations,the distribution entropy of truncated generations and the ratio of average inertia generations were used to evaluate the optimization efficiency of AMSCGA quantificationally.It is shown that the optimization efficiency of AMSCGA is higher than that of genetic algorithm.
基金the Department of Plant Breeding and Genetics,Faculty of Agriculture,University of Agriculture,Faisalabad,Pakistan.
文摘Background:Cotton is known for fiber extraction and it is grown in tropical and sub-tropical areas of the world due to having hot weather.Cotton crop has a significant role in GDP of Pakistan.Therefore,the two-years research was conducted to estimate heritability and association among various yield contributing parameters of cotton,i.e.,plant height,number of bolls per plant,number of sympodial branches per plant,seed cotton yield,boll weight,seed index,ginning outturn(GOT),fiber length,fiber strength,and fiber fineness.Results:Association analysis revealed that seed cotton yield had a significant positive correlation with plant height,number of bolls per plant,number of sympodial branches per plant,GOT,staple length and fiber strength.Staple length and fiber strength were negatively linked with each other.Estimates of heritability were high for all of the traits except the number of sympodial branches per plant and boll weight.Conclusion:The parent IUB-222 was found to be the best for plant height,the number of bolls per plant,boll weight,GOT,seed cotton yield,and seed index.The genotypes namely,NIAB-414 and VH-367 were identified as the best parents for fiber length,strength,and fineness.Among the crosses NIAB-414×IUB-222 was the best for the number of bolls per plant,seed index,seed cotton yield and fiber fineness,whereas,the cross of NIAB-414×CIM-632 was good for plant height.The combination of A555×CIM-632 was the best for the number of sympodial branches per plant,boll weight,fiber length,and strength,and VH-367×CIM-632 proved the best for GOT.
基金supported by the National Natural Science Foundation of China Agriculture(Grant No.2015NWB039)
文摘Background: Gossypium arboreum is a diploid species cultivated in the Old World. It possesses favorable characters that are valuable for developing superior cotton cultivars.Method: A set of 197 Gossypium arboreum accessions were genotyped using 80 genome-wide SSR markers to establish patterns of the genetic diversity and population structure. These accessions were collected from three major G. arboreum growing areas in China. A total of 255 alleles across 80 markers were identified in the genetic diversity analysis.Results: Three subgroups were found using the population structure analysis, corresponding to the Yangtze River Valley, North China, and Southwest China zones of G.arboreum growing areas in China. Average genetic distance and Polymorphic information content value of G. arboreum population were 0.34 and 0.47, respectively, indicating high genetic diversity in the G. arboreum germplasm pool. The Phylogenetic analysis results concurred with the subgroups identified by Structure analysis with a few exceptions. Variations among and within three groups were observed to be 13.61% and 86.39%, respectively.Conclusion: The information regarding genetic diversity and population structure from this study is useful for genetic and genomic analysis and systematic utilization of economically important traits in G. arboreum.
文摘Short sequence repeats(microsatellite,SSR)and expressed sequence tags-SSR(EST-SSR)markers were employed to analyze the genetic diversity of natural colored cotton varieties.AboutShort sequence repeats(microsatellite,SSR)and expressed sequence tags-SSR(EST-SSR)marker s were employed to analyze the genetic diversity of natural colored cotton varieties.About 490 pairs of SSR markers spanning the 26 chro mosomes were selected from the cotton micro satellite data-base,they were composed of the NAU,BNL,MUSS,and CIR markers,and there was one marker every 5 cM on average.
文摘RAPD was used to study the genetic divergency and phylogenetic relationships of five breeds of domestic pigs,including Min pig,Duroc,Yorkshired,Landrace and Junmu I pig.We selected fourteen primers from eighty random primers,caculated genetic distance index matrix and constructed phylogenetic tree with UPGMA methods.Genetic distance index matrix indicated that the genetic relationship between Junmu I pig and Landrace was the closest and the farthest between Duroc and min pig.
基金Project supported by Faculty of Technology,Department of Electrical Engineering,University of Batna,Algeria
文摘This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.
文摘A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar perfofmance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.
基金Project(2011ZK2030)supported by the Soft Science Research Plan of Hunan Province,ChinaProject(2010ZDB42)supported by the Social Science Foundation of Hunan Province,China+1 种基金Projects(09A048,11B070)supported by the Science Research Foundation of Education Bureau of Hunan Province,ChinaProjects(2010GK3036,2011FJ6049)supported by the Science and Technology Plan of Hunan Province,China
文摘As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of closed-loop supply chain was selected as fitness function, and a unique and tidy coding mode was adopted in the proposed algorithm. Then, some mutation and crossover operators were introduced to achieve discrete optimization of RCSCN structure. The simulation results show that the proposed algorithm can gain global optimal solution with good convergent performance and rapidity. The computing speed is only 22.16 s, which is shorter than those of the other optimization algorithms.
