A controversial taxon,Hipparion plocodus,is reviewed in the present study.Hi.plocodus has been confirmed to be a valid species with definite diagnostic characteristics,represented by cranial specimens from Baode,Shanx...A controversial taxon,Hipparion plocodus,is reviewed in the present study.Hi.plocodus has been confirmed to be a valid species with definite diagnostic characteristics,represented by cranial specimens from Baode,Shanxi Province.The phylogenetic analysis performed in the present study,with a new matrix,shows that Hi.plocodus forms a monophyletic group with a European species,Hippotherium malpassii.Actually,no close relationship between so-called Hm.malpassii and the genus Hippotherium has been identified,and the record of stratigraphic range of this genus in late stage of Late Miocene is currently absent.Herein previously Hi.plocodus and Hm.malpassii have both attributed into“Hipparion”before the discovery of better material.Evolutionary stages and correlative absolute age showed that these two species should derive independently from some primitive clade.During the late stage of the Late Miocene,the development of the Asian summer monsoon enhanced the humidity of China,with forest and wood habitats expanding considerably under this setting.As the result,one Eurasian closed-habitat lineage thus extended its range into China,which had become very suited for it,give rise to“Hi.”plocodus.展开更多
Several tritylodontid taxa have been reported from the Upper Jurassic of the Wucaiwan area in the Junggar Basin of Xinjiang,northwestern China,including Yuanotherium minor.The original study described the partially pr...Several tritylodontid taxa have been reported from the Upper Jurassic of the Wucaiwan area in the Junggar Basin of Xinjiang,northwestern China,including Yuanotherium minor.The original study described the partially preserved postcanine teeth in the middle of the left upper maxilla.After detailed re-examination of the specimen and by CT scanning,3D reconstruction,and scanning electron microscopy observations,we provided a more detailed description of the osteology,neurosensory,and tooth wear pattern for all the bones preserved in this specimen and clarified some characters.Based on new information about the cusp wear pattern,the chewing movement pattern of the dentition and detailed cusp morphology,we discussed the cuspal homology of upper cheek teeth of tritylodontids and postulate a standardized method for cusp identification.We hypothesize that the unique maxilla characteristics furnish the evidence for transitional stages about the evolution of the upper jaw-palate structure in tritylodontids.展开更多
An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, m...An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, modified similarity measure was considered to gather nodes having similar characteristics. The similarity measure was needed to contain locafi0nal prices as well as regional coherency. In order to consider the two properties simultaneously, distance measure of fuzzy C-mean algorithm had to be modified. Regional clustering algorithm for interconnected power systems was designed based on the modified fuzzy C-mean algorithm. The proposed algorithm produces proper classification for the interconnected power system and the results are demonstrated in the example of IEEE 39-bus interconnected electricity system.展开更多
Thermal performance was the most important factor in the development of borehole heat exchanger utilizing geothermal energy. The thermal performance was affected by many different design parameters, such as configurat...Thermal performance was the most important factor in the development of borehole heat exchanger utilizing geothermal energy. The thermal performance was affected by many different design parameters, such as configuration type and borehole size of geothermal heat exchanger. These eventually determined the operation and cost efficiency of the geothermal heat exchanger system. The main purpose of this work was to assess the thermal performance of geother^nal heat exchanger with variation of borehole sizes and numbers of U-tubes inside a borehole. For this, a thermal response test rig was established with line-source theory. The thermal response test was performed with in-line variable input heat source. Effective thermal conductivity and thermal resistance were obtained from the measured data. From the measurement, the effective thermal conductivity is found to have similar values for two- pair type （4 U-tubes） and three-pair type （6 U-tubes） borehole heat exchanger systems indicating similar heat transfer ability. Meanwhile, the thermal resistance shows lower value for the three-pair type compared to the two-pair type. Measured data based resistance have lower value compared to computed result from design programs. Overall comparison finds better thermal performance for the three-pair type, however, fluctuating temperature variation indicates complex flow behavior inside the borehole and requires further study on flow characteristics.展开更多
Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanc...Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanced k-nearest neighbor(AKNN)method and balanced binary tree(AVL) data structure to improve the prediction accuracy. The AKNN method uses pattern recognition two times in the searching process, which considers the previous sequences of traffic flow to forecast the future traffic state. Clustering method and balanced binary tree technique are introduced to build case database to reduce the searching time. To illustrate the effects of these developments, the accuracies performance of AKNN-AVL method, k-nearest neighbor(KNN) method and the auto-regressive and moving average(ARMA) method are compared. These methods are calibrated and evaluated by the real-time data from a freeway traffic detector near North 3rd Ring Road in Beijing under both normal and incident traffic conditions.The comparisons show that the AKNN-AVL method with the optimal neighbor and pattern size outperforms both KNN method and ARMA method under both normal and incident traffic conditions. In addition, the combinations of clustering method and balanced binary tree technique to the prediction method can increase the searching speed and respond rapidly to case database fluctuations.展开更多
The characteristic of geographic information system（GfS） spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GI...The characteristic of geographic information system（GfS） spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GIS spatial data was proposed in this paper. According to the aggregation of clustering method, R-tree was used to construct rules and specialty of spatial data. HCR-tree was the R-tree built with HCR algorithm. To test the efficiency of HCR algorithm, it was applied not only to the data organization of static R-tree but also to the nodes splitting of dynamic R-tree. The results show that R-tree with HCR has some advantages such as higher searching efficiency, less disk accesses and so on.展开更多
A shadow detection method using pulse couple neural network inspired by the characters of human visual system is proposed.More precisely,lateral inhibition of human vision and coefficient of variation are combined tog...A shadow detection method using pulse couple neural network inspired by the characters of human visual system is proposed.More precisely,lateral inhibition of human vision and coefficient of variation are combined together to improve the pulse couple neural network.Shadow detection is considered to be a shadow region segmentation problem.Experiment shows that the presented method is consistent with human vision compared to shadow detection methods based on HSV and pulse couple neural network(PCNN) by both subjective and objective assessments.展开更多
A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy syst...A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy system, and an improved subtractive clustering algorithm in the fuzzy-rule-selecting phase. The weights obtained in PRM, which gives protection against noise and outliers, were incorporated into the potential measure of the subtractive cluster algorithm to enhance the robustness of the fuzzy rule cluster process, and a compact Mamdani-type fuzzy system was established after the parameters in the consequent parts of rules were re-estimated by partial least squares(PLS). The main characteristics of the new approach were its simplicity and ability to construct fuzzy system fast and robustly. Simulation and experiment results show that the proposed approach can achieve satisfactory results in various kinds of data domains with noise and outliers. Compared with D-SVD and ARRBFN, the proposed approach yields much fewer rules and less RMSE values.展开更多
In order to improve the resource allocation mechanism of artificial immune recognition system(AIRS) and decrease the memory cells,a fuzzy logic resource allocation and memory cell pruning based AIRS(FPAIRS) is propose...In order to improve the resource allocation mechanism of artificial immune recognition system(AIRS) and decrease the memory cells,a fuzzy logic resource allocation and memory cell pruning based AIRS(FPAIRS) is proposed.In FPAIRS,the fuzzy logic is determined by a parameter,thus,the optimal fuzzy logics for different problems can be located through changing the parameter value.At the same time,the memory cells of low fitness scores are pruned to improve the classifier.This classifier was compared with other classifiers on six UCI datasets classification performance.The results show that the accuracies reached by FPAIRS are higher than or comparable to the accuracies of other classifiers,and the memory cells decrease when compared with the memory cells of AIRS.The results show that the algorithm is a high-performance classifier.展开更多
Category-based statistic language model is an important method to solve the problem of sparse data.But there are two bottlenecks:1) The problem of word clustering.It is hard to find a suitable clustering method with g...Category-based statistic language model is an important method to solve the problem of sparse data.But there are two bottlenecks:1) The problem of word clustering.It is hard to find a suitable clustering method with good performance and less computation.2) Class-based method always loses the prediction ability to adapt the text in different domains.In order to solve above problems,a definition of word similarity by utilizing mutual information was presented.Based on word similarity,the definition of word set similarity was given.Experiments show that word clustering algorithm based on similarity is better than conventional greedy clustering method in speed and performance,and the perplexity is reduced from 283 to 218.At the same time,an absolute weighted difference method was presented and was used to construct vari-gram language model which has good prediction ability.The perplexity of vari-gram model is reduced from 234.65 to 219.14 on Chinese corpora,and is reduced from 195.56 to 184.25 on English corpora compared with category-based model.展开更多
To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before app...To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before applying the forecasting techniques, a support vector classifier was first used to classify the data, and then the filtering was used to create separate trend and volatility sequences. After forecasting, the Markov chain transition probability matrix was introduced to adjust the residual. Simulation results using surplus gas data from an iron and steel enterprise demonstrate that the constructed SVC-HP-ENN-LSSVM-MC prediction model prediction is accurate, and that the classification accuracy is high under different conditions. Based on this, the scheduling model was constructed for surplus gas operating, and it has been used to investigate the comprehensive measures for managing the operational probabilistic risk and optimize the economic benefit at various working conditions and implementations. It has extended the concepts of traditional surplus gas dispatching systems, and provides a method for enterprises to determine optimal schedules.展开更多
文摘A controversial taxon,Hipparion plocodus,is reviewed in the present study.Hi.plocodus has been confirmed to be a valid species with definite diagnostic characteristics,represented by cranial specimens from Baode,Shanxi Province.The phylogenetic analysis performed in the present study,with a new matrix,shows that Hi.plocodus forms a monophyletic group with a European species,Hippotherium malpassii.Actually,no close relationship between so-called Hm.malpassii and the genus Hippotherium has been identified,and the record of stratigraphic range of this genus in late stage of Late Miocene is currently absent.Herein previously Hi.plocodus and Hm.malpassii have both attributed into“Hipparion”before the discovery of better material.Evolutionary stages and correlative absolute age showed that these two species should derive independently from some primitive clade.During the late stage of the Late Miocene,the development of the Asian summer monsoon enhanced the humidity of China,with forest and wood habitats expanding considerably under this setting.As the result,one Eurasian closed-habitat lineage thus extended its range into China,which had become very suited for it,give rise to“Hi.”plocodus.
文摘Several tritylodontid taxa have been reported from the Upper Jurassic of the Wucaiwan area in the Junggar Basin of Xinjiang,northwestern China,including Yuanotherium minor.The original study described the partially preserved postcanine teeth in the middle of the left upper maxilla.After detailed re-examination of the specimen and by CT scanning,3D reconstruction,and scanning electron microscopy observations,we provided a more detailed description of the osteology,neurosensory,and tooth wear pattern for all the bones preserved in this specimen and clarified some characters.Based on new information about the cusp wear pattern,the chewing movement pattern of the dentition and detailed cusp morphology,we discussed the cuspal homology of upper cheek teeth of tritylodontids and postulate a standardized method for cusp identification.We hypothesize that the unique maxilla characteristics furnish the evidence for transitional stages about the evolution of the upper jaw-palate structure in tritylodontids.
基金Work supported by the Second Stage of Brain Korea 21 ProjectsWork(2010-0020163) supported by Priority Research Centers Program through the National Research Foundation (NRF) funded by the Ministry of Education,Science and Technology of Korea
文摘An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, modified similarity measure was considered to gather nodes having similar characteristics. The similarity measure was needed to contain locafi0nal prices as well as regional coherency. In order to consider the two properties simultaneously, distance measure of fuzzy C-mean algorithm had to be modified. Regional clustering algorithm for interconnected power systems was designed based on the modified fuzzy C-mean algorithm. The proposed algorithm produces proper classification for the interconnected power system and the results are demonstrated in the example of IEEE 39-bus interconnected electricity system.
基金Project financially supported by the Second Stage of Brain Korea 21 Projects and Changwon National University,Korea
文摘Thermal performance was the most important factor in the development of borehole heat exchanger utilizing geothermal energy. The thermal performance was affected by many different design parameters, such as configuration type and borehole size of geothermal heat exchanger. These eventually determined the operation and cost efficiency of the geothermal heat exchanger system. The main purpose of this work was to assess the thermal performance of geother^nal heat exchanger with variation of borehole sizes and numbers of U-tubes inside a borehole. For this, a thermal response test rig was established with line-source theory. The thermal response test was performed with in-line variable input heat source. Effective thermal conductivity and thermal resistance were obtained from the measured data. From the measurement, the effective thermal conductivity is found to have similar values for two- pair type （4 U-tubes） and three-pair type （6 U-tubes） borehole heat exchanger systems indicating similar heat transfer ability. Meanwhile, the thermal resistance shows lower value for the three-pair type compared to the two-pair type. Measured data based resistance have lower value compared to computed result from design programs. Overall comparison finds better thermal performance for the three-pair type, however, fluctuating temperature variation indicates complex flow behavior inside the borehole and requires further study on flow characteristics.
基金Project(2012CB725403)supported by the National Basic Research Program of ChinaProjects(71210001,51338008)supported by the National Natural Science Foundation of ChinaProject supported by World Capital Cities Smooth Traffic Collaborative Innovation Center and Singapore National Research Foundation Under Its Campus for Research Excellence and Technology Enterprise(CREATE)Programme
文摘Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanced k-nearest neighbor(AKNN)method and balanced binary tree(AVL) data structure to improve the prediction accuracy. The AKNN method uses pattern recognition two times in the searching process, which considers the previous sequences of traffic flow to forecast the future traffic state. Clustering method and balanced binary tree technique are introduced to build case database to reduce the searching time. To illustrate the effects of these developments, the accuracies performance of AKNN-AVL method, k-nearest neighbor(KNN) method and the auto-regressive and moving average(ARMA) method are compared. These methods are calibrated and evaluated by the real-time data from a freeway traffic detector near North 3rd Ring Road in Beijing under both normal and incident traffic conditions.The comparisons show that the AKNN-AVL method with the optimal neighbor and pattern size outperforms both KNN method and ARMA method under both normal and incident traffic conditions. In addition, the combinations of clustering method and balanced binary tree technique to the prediction method can increase the searching speed and respond rapidly to case database fluctuations.
文摘The characteristic of geographic information system（GfS） spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GIS spatial data was proposed in this paper. According to the aggregation of clustering method, R-tree was used to construct rules and specialty of spatial data. HCR-tree was the R-tree built with HCR algorithm. To test the efficiency of HCR algorithm, it was applied not only to the data organization of static R-tree but also to the nodes splitting of dynamic R-tree. The results show that R-tree with HCR has some advantages such as higher searching efficiency, less disk accesses and so on.
基金Projects(61262032,61173122)supported by the National Natural Science Foundation of ChinaProject(12JJ038)supported by the Key Project of Natural Science Foundation of Hunan Province,China+1 种基金Project(2012FJ3100)supported by the Hunan Provincial Science&Technology Department,ChinaProject(12B103)supported by the Youth Project of Hunan Universities and Colleges Science Research,China
文摘A shadow detection method using pulse couple neural network inspired by the characters of human visual system is proposed.More precisely,lateral inhibition of human vision and coefficient of variation are combined together to improve the pulse couple neural network.Shadow detection is considered to be a shadow region segmentation problem.Experiment shows that the presented method is consistent with human vision compared to shadow detection methods based on HSV and pulse couple neural network(PCNN) by both subjective and objective assessments.
基金Project(61473298)supported by the National Natural Science Foundation of ChinaProject(2015QNA65)supported by Fundamental Research Funds for the Central Universities,China
文摘A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy system, and an improved subtractive clustering algorithm in the fuzzy-rule-selecting phase. The weights obtained in PRM, which gives protection against noise and outliers, were incorporated into the potential measure of the subtractive cluster algorithm to enhance the robustness of the fuzzy rule cluster process, and a compact Mamdani-type fuzzy system was established after the parameters in the consequent parts of rules were re-estimated by partial least squares(PLS). The main characteristics of the new approach were its simplicity and ability to construct fuzzy system fast and robustly. Simulation and experiment results show that the proposed approach can achieve satisfactory results in various kinds of data domains with noise and outliers. Compared with D-SVD and ARRBFN, the proposed approach yields much fewer rules and less RMSE values.
基金Project(61170199)supported by the National Natural Science Foundation of ChinaProject(11A004)support by the Scientific Research Fund of Education Department of Hunan Province,China
文摘In order to improve the resource allocation mechanism of artificial immune recognition system(AIRS) and decrease the memory cells,a fuzzy logic resource allocation and memory cell pruning based AIRS(FPAIRS) is proposed.In FPAIRS,the fuzzy logic is determined by a parameter,thus,the optimal fuzzy logics for different problems can be located through changing the parameter value.At the same time,the memory cells of low fitness scores are pruned to improve the classifier.This classifier was compared with other classifiers on six UCI datasets classification performance.The results show that the accuracies reached by FPAIRS are higher than or comparable to the accuracies of other classifiers,and the memory cells decrease when compared with the memory cells of AIRS.The results show that the algorithm is a high-performance classifier.
基金Project(60763001) supported by the National Natural Science Foundation of ChinaProject(2010GZS0072) supported by the Natural Science Foundation of Jiangxi Province,ChinaProject(GJJ12271) supported by the Science and Technology Foundation of Provincial Education Department of Jiangxi Province,China
文摘Category-based statistic language model is an important method to solve the problem of sparse data.But there are two bottlenecks:1) The problem of word clustering.It is hard to find a suitable clustering method with good performance and less computation.2) Class-based method always loses the prediction ability to adapt the text in different domains.In order to solve above problems,a definition of word similarity by utilizing mutual information was presented.Based on word similarity,the definition of word set similarity was given.Experiments show that word clustering algorithm based on similarity is better than conventional greedy clustering method in speed and performance,and the perplexity is reduced from 283 to 218.At the same time,an absolute weighted difference method was presented and was used to construct vari-gram language model which has good prediction ability.The perplexity of vari-gram model is reduced from 234.65 to 219.14 on Chinese corpora,and is reduced from 195.56 to 184.25 on English corpora compared with category-based model.
基金Project(51204082)supported by the National Natural Science Foundation of ChinaProject(KKSY201458118)supported by the Talent Cultivation Project of Kuning University of Science and Technology,China
文摘To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before applying the forecasting techniques, a support vector classifier was first used to classify the data, and then the filtering was used to create separate trend and volatility sequences. After forecasting, the Markov chain transition probability matrix was introduced to adjust the residual. Simulation results using surplus gas data from an iron and steel enterprise demonstrate that the constructed SVC-HP-ENN-LSSVM-MC prediction model prediction is accurate, and that the classification accuracy is high under different conditions. Based on this, the scheduling model was constructed for surplus gas operating, and it has been used to investigate the comprehensive measures for managing the operational probabilistic risk and optimize the economic benefit at various working conditions and implementations. It has extended the concepts of traditional surplus gas dispatching systems, and provides a method for enterprises to determine optimal schedules.
