To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on be...To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on belief rule structure is proposed.By defining the continuous probabilistic hesitation fuzzy linguistic term sets(CPHFLTS)and establishing CPHFLTS distance measure,the belief rule base of the relationship between feature space and category space is constructed through information integration,and the evidence reasoning of the input samples is carried out.The experimental results show that the proposed method can make full use of sensor data and expert knowledge for recognition.Compared with the other methods,the proposed method has a higher correct recognition rate under different noise levels.展开更多
Fuzzy entropy was designed for non convex fuzzy membership function using well known Hamming distance measure.The proposed fuzzy entropy had the same structure as that of convex fuzzy membership case.Design procedure ...Fuzzy entropy was designed for non convex fuzzy membership function using well known Hamming distance measure.The proposed fuzzy entropy had the same structure as that of convex fuzzy membership case.Design procedure of fuzzy entropy was proposed by considering fuzzy membership through distance measure,and the obtained results contained more flexibility than the general fuzzy membership function.Furthermore,characteristic analyses for non convex function were also illustrated.Analyses on the mutual information were carried out through the proposed fuzzy entropy and similarity measure,which was also dual structure of fuzzy entropy.By the illustrative example,mutual information was discussed.展开更多
The evolution in communication techniques has created wide threats for crucial information transfer through a communication channel. Covert communication with steganography is a skill of concealing secret information ...The evolution in communication techniques has created wide threats for crucial information transfer through a communication channel. Covert communication with steganography is a skill of concealing secret information within cover object and hence shields the data theft over rapidly growing network.Recently, diverse steganography techniques using edge identification have been proposed in literature.Numerous methods however utilize certain pixels in the cover image for inserting edge information,resulting in significant deformation. The conventional edge detection method limits the deployment of edge detection in steganography as concealing the information would introduce some variations to the cover image. Hence inserting data in pixel areas recognized by existing conventional edge detection techniques like canny cannot ensure the recognition of the exact edge locations for the cover and stego images. In this paper, an Adaptive steganography method based on novel fuzzy edge identification is proposed. The method proposed is proficient of estimating the precise edge areas of a cover image and also ensures the exact edge location after embedding the secret message. Experimental results reveal that the technique has attained good imperceptibility compared to the Hayat AI-Dmour and Ahmed AIAni Edge XOR method in spatial domain.展开更多
In practical multi-sensor information fusion systems, there exists uncertainty about the network structure, active state of sensors, and information itself （including fuzziness, randomness, incompleteness as well as ...In practical multi-sensor information fusion systems, there exists uncertainty about the network structure, active state of sensors, and information itself （including fuzziness, randomness, incompleteness as well as roughness, etc）. Hence it requires investigating the problem of uncertain information fusion. Robust learning algorithm which adapts to complex environment and the fuzzy inference algorithm which disposes fuzzy information are explored to solve the problem. Based on the fusion technology of neural networks and fuzzy inference algorithm, a multi-sensor uncertain information fusion system is modeled. Also RANFIS learning algorithm and fusing weight synthesized inference algorithm are developed from the ANFIS algorithm according to the concept of robust neural networks. This fusion system mainly consists of RANFIS confidence estimator, fusing weight synthesized inference knowledge base and weighted fusion section. The simulation result demonstrates that the proposed fusion model and algorithm have the capability of uncertain information fusion, thus is obviously advantageous compared with the conventional Kalman weighted fusion algorithm.展开更多
The weights of criteria are incompletely known and the criteria values are incomplete and uncertain or even default in some fuzzy multi-criteria decision-making problems.For those problems,an approach based on evident...The weights of criteria are incompletely known and the criteria values are incomplete and uncertain or even default in some fuzzy multi-criteria decision-making problems.For those problems,an approach based on evidential reasoning is proposed,in which the criteria values are integrated on the basis of analytical algorithm of evidential reasoning,and then nonlinear programming models of each alternative are developed with the incomplete information on weights.The genetic algorithm is employed to solve the models,producing the weights and the utility interval of each alternative,and the ranking of the whole set of alternatives can be attained.Finally,an example shows the effectiveness of the method.展开更多
The concept of rough communication based on both-branch fuzzy set is proposed, in which the loss of information may exist, for each agent there has a different language and can not provide precise communication to eac...The concept of rough communication based on both-branch fuzzy set is proposed, in which the loss of information may exist, for each agent there has a different language and can not provide precise communication to each other. The method of information measure in a rough communication based on both-branch fuzzy set is proposed. By using some concepts, such as ｜α｜-both-branch rough communication cut, the relation theorem between rough communication based on both-branch fuzzy concept and rough communication based on classical concept is obtained. Finally, an example of rough communication based on both-branch fuzzy set is given.展开更多
This study aims to reflect the information coverage grey number and the interaction between attributes in grey relational decision making. Therefore, a multi-attribute decision method based on the grey information cov...This study aims to reflect the information coverage grey number and the interaction between attributes in grey relational decision making. Therefore, a multi-attribute decision method based on the grey information coverage interaction relational degree(GIRD) is proposed. Firstly, this paper defines the information coverage grey number, and establishes the GIRD model by using the Choquet fuzzy integral and grey relational principle. It proves that the proposed model not only is the general and unified form of the point relational degree, interval relational degree, mixed relational degree and grey fuzzy integral relational degree, but also can effectively deal with the interaction between attributes. Further,a decision making example of evaluating the industrial operation quality for 14 cities in Hunan province of China is provided to highlight the implementation, availability, and feasibility of the proposed decision model.展开更多
基金This work was supported by the Youth Foundation of National Science Foundation of China(62001503)the Special Fund for Taishan Scholar Project(ts 201712072).
文摘To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on belief rule structure is proposed.By defining the continuous probabilistic hesitation fuzzy linguistic term sets(CPHFLTS)and establishing CPHFLTS distance measure,the belief rule base of the relationship between feature space and category space is constructed through information integration,and the evidence reasoning of the input samples is carried out.The experimental results show that the proposed method can make full use of sensor data and expert knowledge for recognition.Compared with the other methods,the proposed method has a higher correct recognition rate under different noise levels.
基金Work supported by the Second Stage of Brain Korea 21 Projects Work(2010-0020163) supported by the Priority Research Centers Program through the National Research Foundation (NRF) funded by the Ministry of Education,Science and Technology of Korea
文摘Fuzzy entropy was designed for non convex fuzzy membership function using well known Hamming distance measure.The proposed fuzzy entropy had the same structure as that of convex fuzzy membership case.Design procedure of fuzzy entropy was proposed by considering fuzzy membership through distance measure,and the obtained results contained more flexibility than the general fuzzy membership function.Furthermore,characteristic analyses for non convex function were also illustrated.Analyses on the mutual information were carried out through the proposed fuzzy entropy and similarity measure,which was also dual structure of fuzzy entropy.By the illustrative example,mutual information was discussed.
文摘The evolution in communication techniques has created wide threats for crucial information transfer through a communication channel. Covert communication with steganography is a skill of concealing secret information within cover object and hence shields the data theft over rapidly growing network.Recently, diverse steganography techniques using edge identification have been proposed in literature.Numerous methods however utilize certain pixels in the cover image for inserting edge information,resulting in significant deformation. The conventional edge detection method limits the deployment of edge detection in steganography as concealing the information would introduce some variations to the cover image. Hence inserting data in pixel areas recognized by existing conventional edge detection techniques like canny cannot ensure the recognition of the exact edge locations for the cover and stego images. In this paper, an Adaptive steganography method based on novel fuzzy edge identification is proposed. The method proposed is proficient of estimating the precise edge areas of a cover image and also ensures the exact edge location after embedding the secret message. Experimental results reveal that the technique has attained good imperceptibility compared to the Hayat AI-Dmour and Ahmed AIAni Edge XOR method in spatial domain.
基金This project was supported by the National Natural Science Foundation of China (60572038)
文摘In practical multi-sensor information fusion systems, there exists uncertainty about the network structure, active state of sensors, and information itself （including fuzziness, randomness, incompleteness as well as roughness, etc）. Hence it requires investigating the problem of uncertain information fusion. Robust learning algorithm which adapts to complex environment and the fuzzy inference algorithm which disposes fuzzy information are explored to solve the problem. Based on the fusion technology of neural networks and fuzzy inference algorithm, a multi-sensor uncertain information fusion system is modeled. Also RANFIS learning algorithm and fusing weight synthesized inference algorithm are developed from the ANFIS algorithm according to the concept of robust neural networks. This fusion system mainly consists of RANFIS confidence estimator, fusing weight synthesized inference knowledge base and weighted fusion section. The simulation result demonstrates that the proposed fusion model and algorithm have the capability of uncertain information fusion, thus is obviously advantageous compared with the conventional Kalman weighted fusion algorithm.
基金supported by the National Natural Science Foundation of China(7077111570921001)and Key Project of National Natural Science Foundation of China(70631004)
文摘The weights of criteria are incompletely known and the criteria values are incomplete and uncertain or even default in some fuzzy multi-criteria decision-making problems.For those problems,an approach based on evidential reasoning is proposed,in which the criteria values are integrated on the basis of analytical algorithm of evidential reasoning,and then nonlinear programming models of each alternative are developed with the incomplete information on weights.The genetic algorithm is employed to solve the models,producing the weights and the utility interval of each alternative,and the ranking of the whole set of alternatives can be attained.Finally,an example shows the effectiveness of the method.
基金Supported by Gansu Province Natural Science Foundation（3ZS061-A25-045）, and the“Qing Lan”Talent Engineering Funds of Lanazhou Jiaotong University（QL-06-19A）
基金supported by the National Natural Science Foundation of China (61070241)the Natural Science Foundation of Shandong Province (ZR2010 FM035)the Science Research Foundation of University of Jinan (XKYK31)
文摘The concept of rough communication based on both-branch fuzzy set is proposed, in which the loss of information may exist, for each agent there has a different language and can not provide precise communication to each other. The method of information measure in a rough communication based on both-branch fuzzy set is proposed. By using some concepts, such as ｜α｜-both-branch rough communication cut, the relation theorem between rough communication based on both-branch fuzzy concept and rough communication based on classical concept is obtained. Finally, an example of rough communication based on both-branch fuzzy set is given.
基金supported by the National Natural Science Foundation of China(71871174,71571065,71671135)the National Social Science Fund of China(13FGL005)。
文摘This study aims to reflect the information coverage grey number and the interaction between attributes in grey relational decision making. Therefore, a multi-attribute decision method based on the grey information coverage interaction relational degree(GIRD) is proposed. Firstly, this paper defines the information coverage grey number, and establishes the GIRD model by using the Choquet fuzzy integral and grey relational principle. It proves that the proposed model not only is the general and unified form of the point relational degree, interval relational degree, mixed relational degree and grey fuzzy integral relational degree, but also can effectively deal with the interaction between attributes. Further,a decision making example of evaluating the industrial operation quality for 14 cities in Hunan province of China is provided to highlight the implementation, availability, and feasibility of the proposed decision model.
