To smooth the correlation process from bio-virus diffusion to emergency relief response,the Gaussian plume model is used to describe the diffusion of dangerous sources,where the bio-virus concentration at any given po...To smooth the correlation process from bio-virus diffusion to emergency relief response,the Gaussian plume model is used to describe the diffusion of dangerous sources,where the bio-virus concentration at any given point in affected areas can be calculated.And the toxic load rule is introduced to define the borderline of the dangerous area at different levels.Combined with this,different emergency levels of different demand points in dangerous areas are confirmed using fuzzy clustering,which allows demand points at the same emergency level to cluster in a group.Some effective emergency relief centers are chosen from the candidate hospitals which are located in different emergency level affected areas by set covering.Bioterrorism experiments which were conducted in Nanjing,Jiangsu province are simulated,and the results indicate that the novel method can be used efficiently by decision makers during an actual anti-bioterrorism relief.展开更多
In order to accurately describe the dynamic characteristics of flight vehicles through aerodynamic modeling, an adaptive wavelet neural network (AWNN) aerodynamic modeling method is proposed, based on subset kernel pr...In order to accurately describe the dynamic characteristics of flight vehicles through aerodynamic modeling, an adaptive wavelet neural network (AWNN) aerodynamic modeling method is proposed, based on subset kernel principal components analysis (SKPCA) feature extraction. Firstly, by fuzzy C-means clustering, some samples are selected from the training sample set to constitute a sample subset. Then, the obtained samples subset is used to execute SKPCA for extracting basic features of the training samples. Finally, using the extracted basic features, the AWNN aerodynamic model is established. The experimental results show that, in 50 times repetitive modeling, the modeling ability of the method proposed is better than that of other six methods. It only needs about half the modeling time of KPCA-AWNN under a close prediction accuracy, and can easily determine the model parameters. This enables it to be effective and feasible to construct the aerodynamic modeling for flight vehicles.展开更多
This paper introduces the calculation of the deformation of the surroundings of roadways and the division of surroundings into 5 levels by means of fuzzy integral assess matrix, which serves as the scientific basis fo...This paper introduces the calculation of the deformation of the surroundings of roadways and the division of surroundings into 5 levels by means of fuzzy integral assess matrix, which serves as the scientific basis for selecting supporting pattern of roadways and determining the parameters of support.展开更多
In a special case of type-2 fuzzy logic systems （FLS）, i.e. geometric inteIval type-2 fuzzy logic systems （GIT-2FLS）, the crisp output is obtained by computing the geometric center of footprint of uncertainly （FO...In a special case of type-2 fuzzy logic systems （FLS）, i.e. geometric inteIval type-2 fuzzy logic systems （GIT-2FLS）, the crisp output is obtained by computing the geometric center of footprint of uncertainly （FOU） without type-reduction, but the defuzzifying method acts against the corner concepts of type-2 fuzzy sets in some cases. In this paper, a PSO type-reduction method for GIT-2FLS based on the particle swarm optimization （PSO） algorithm is presented. With the PSO type-reduction, the inference principle of geometric interval FLS operating on the continuous domain is consistent with that of traditional interval type-2 FLS operating on the discrete domain. With comparative experiments, it is proved that the PSO type-reduction exhibits good performance, and is a satisfactory complement for the theory of GIT-2FLS.展开更多
The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is conside...The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is considered a vital process. The data analysis process consists of different tasks, among which the data stream classification approaches face more challenges than the other commonly used techniques. Even though the classification is a continuous process, it requires a design that can adapt the classification model so as to adjust the concept change or the boundary change between the classes. Hence, we design a novel fuzzy classifier known as THRFuzzy to classify new incoming data streams. Rough set theory along with tangential holoentropy function helps in the designing the dynamic classification model. The classification approach uses kernel fuzzy c-means(FCM) clustering for the generation of the rules and tangential holoentropy function to update the membership function. The performance of the proposed THRFuzzy method is verified using three datasets, namely skin segmentation, localization, and breast cancer datasets, and the evaluated metrics, accuracy and time, comparing its performance with HRFuzzy and adaptive k-NN classifiers. The experimental results conclude that THRFuzzy classifier shows better classification results providing a maximum accuracy consuming a minimal time than the existing classifiers.展开更多
This study presents a novel approach to evaluate the rate of aggregate risk of Invasive Alien Plant Species. Using risk values and grade of importance of weights of risk factors which may reflect invasiveness of plant...This study presents a novel approach to evaluate the rate of aggregate risk of Invasive Alien Plant Species. Using risk values and grade of importance of weights of risk factors which may reflect invasiveness of plant species are considered. We use Linguistic Ordered Weighted Averaging operator to evaluate the grade of important of weights. Since the risk values and important weights are identified from two different linguistic term sets, fuzzy set theory techniques were used to combine the two sets. The rates obtained from the model were compared with NRA risk levels and the model was validated with data from known and non-invasive species. The model is improved by weighting the risk values of risk factors. The improved model produced significant results and resulted a better tracking system for identifying potential invaders than the conventional risk assessment.展开更多
基金The National Natural Science Foundation of China(No.70671021)the National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAH02A06)
文摘To smooth the correlation process from bio-virus diffusion to emergency relief response,the Gaussian plume model is used to describe the diffusion of dangerous sources,where the bio-virus concentration at any given point in affected areas can be calculated.And the toxic load rule is introduced to define the borderline of the dangerous area at different levels.Combined with this,different emergency levels of different demand points in dangerous areas are confirmed using fuzzy clustering,which allows demand points at the same emergency level to cluster in a group.Some effective emergency relief centers are chosen from the candidate hospitals which are located in different emergency level affected areas by set covering.Bioterrorism experiments which were conducted in Nanjing,Jiangsu province are simulated,and the results indicate that the novel method can be used efficiently by decision makers during an actual anti-bioterrorism relief.
基金Project(51209167) supported by Youth Project of the National Natural Science Foundation of ChinaProject(2012JM8026) supported by Shaanxi Provincial Natural Science Foundation, China
文摘In order to accurately describe the dynamic characteristics of flight vehicles through aerodynamic modeling, an adaptive wavelet neural network (AWNN) aerodynamic modeling method is proposed, based on subset kernel principal components analysis (SKPCA) feature extraction. Firstly, by fuzzy C-means clustering, some samples are selected from the training sample set to constitute a sample subset. Then, the obtained samples subset is used to execute SKPCA for extracting basic features of the training samples. Finally, using the extracted basic features, the AWNN aerodynamic model is established. The experimental results show that, in 50 times repetitive modeling, the modeling ability of the method proposed is better than that of other six methods. It only needs about half the modeling time of KPCA-AWNN under a close prediction accuracy, and can easily determine the model parameters. This enables it to be effective and feasible to construct the aerodynamic modeling for flight vehicles.
文摘This paper introduces the calculation of the deformation of the surroundings of roadways and the division of surroundings into 5 levels by means of fuzzy integral assess matrix, which serves as the scientific basis for selecting supporting pattern of roadways and determining the parameters of support.
基金Sponsored by the National Hi-Tech Program of China(Grant No. 2005AA420050)the National Key Technology R&D Program of China(Grant No.2006BAD10A0401, 2006BAH02A01)
文摘In a special case of type-2 fuzzy logic systems （FLS）, i.e. geometric inteIval type-2 fuzzy logic systems （GIT-2FLS）, the crisp output is obtained by computing the geometric center of footprint of uncertainly （FOU） without type-reduction, but the defuzzifying method acts against the corner concepts of type-2 fuzzy sets in some cases. In this paper, a PSO type-reduction method for GIT-2FLS based on the particle swarm optimization （PSO） algorithm is presented. With the PSO type-reduction, the inference principle of geometric interval FLS operating on the continuous domain is consistent with that of traditional interval type-2 FLS operating on the discrete domain. With comparative experiments, it is proved that the PSO type-reduction exhibits good performance, and is a satisfactory complement for the theory of GIT-2FLS.
基金supported by proposal No.OSD/BCUD/392/197 Board of Colleges and University Development,Savitribai Phule Pune University,Pune
文摘The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is considered a vital process. The data analysis process consists of different tasks, among which the data stream classification approaches face more challenges than the other commonly used techniques. Even though the classification is a continuous process, it requires a design that can adapt the classification model so as to adjust the concept change or the boundary change between the classes. Hence, we design a novel fuzzy classifier known as THRFuzzy to classify new incoming data streams. Rough set theory along with tangential holoentropy function helps in the designing the dynamic classification model. The classification approach uses kernel fuzzy c-means(FCM) clustering for the generation of the rules and tangential holoentropy function to update the membership function. The performance of the proposed THRFuzzy method is verified using three datasets, namely skin segmentation, localization, and breast cancer datasets, and the evaluated metrics, accuracy and time, comparing its performance with HRFuzzy and adaptive k-NN classifiers. The experimental results conclude that THRFuzzy classifier shows better classification results providing a maximum accuracy consuming a minimal time than the existing classifiers.
文摘This study presents a novel approach to evaluate the rate of aggregate risk of Invasive Alien Plant Species. Using risk values and grade of importance of weights of risk factors which may reflect invasiveness of plant species are considered. We use Linguistic Ordered Weighted Averaging operator to evaluate the grade of important of weights. Since the risk values and important weights are identified from two different linguistic term sets, fuzzy set theory techniques were used to combine the two sets. The rates obtained from the model were compared with NRA risk levels and the model was validated with data from known and non-invasive species. The model is improved by weighting the risk values of risk factors. The improved model produced significant results and resulted a better tracking system for identifying potential invaders than the conventional risk assessment.
