Aim To improve the causal diagnosis method presented by Bandekar and propose a new method of finding the root fault order according to the fault possibility by means of numerical calculation. Methods Based on the ca...Aim To improve the causal diagnosis method presented by Bandekar and propose a new method of finding the root fault order according to the fault possibility by means of numerical calculation. Methods Based on the causal graph, by utilization of fuzzified threshold value and fuzzy discrimination matrix, a kind of fuzzy causal diagnosis method was given and the fault possibility of each elements in the root fault candidate set (RFCS) was obtained. Results and Conclusion The order of each element in the RFCS can be obtained by the fault possibility, which makes the location of fault much easier. The diagnosis speed of this method is quite high, and by means of the fuzzified threshold value and fuzzy discrimination matrix, the result is more robust to noises and bad parameter's choice.展开更多
A novel fuzzy linear discriminant analysis method by the canonical correlation analysis (fuzzy-LDA/CCA)is presented and applied to the facial expression recognition. The fuzzy method is used to evaluate the degree o...A novel fuzzy linear discriminant analysis method by the canonical correlation analysis (fuzzy-LDA/CCA)is presented and applied to the facial expression recognition. The fuzzy method is used to evaluate the degree of the class membership to which each training sample belongs. CCA is then used to establish the relationship between each facial image and the corresponding class membership vector, and the class membership vector of a test image is estimated using this relationship. Moreover, the fuzzy-LDA/CCA method is also generalized to deal with nonlinear discriminant analysis problems via kernel method. The performance of the proposed method is demonstrated using real data.展开更多
In order to improve the infrared detection and discrimination ability of the smart munition to the dynamic armor target under the complex background,the multi-line array infrared detection system is established based ...In order to improve the infrared detection and discrimination ability of the smart munition to the dynamic armor target under the complex background,the multi-line array infrared detection system is established based on the combination of the single unit infrared detector.The surface dimension features of ground armored targets are identified by size calculating solution algorithm.The signal response value and the value of size calculating are identified by the method of fuzzy recognition to make the fuzzy classification judgment for armored target.According to the characteristics of the target signal,a custom threshold de-noising function is proposed to solve the problem of signal preprocessing.The multi-line array infrared detection can complete the scanning detection in a large area in a short time with the characteristics of smart munition in the steady-state scanning stage.The method solves the disadvantages of wide scanning interval and low detection probability of single unit infrared detection.By reducing the scanning interval,the number of random rendezvous in the infrared feature area of the upper surface is increased,the accuracy of the size calculating is guaranteed.The experiments results show that in the fuzzy recognition method,the size calculating is introduced as the feature operator,which can improve the recognition ability of the ground armor target with different shape size.展开更多
Excessive pesticide residues on Chinese cabbage will be harmful to people’s health.Therefore,an identification system was designed for qualitative analysis of lambda-cyhalothrin residues on Chinese cabbage leaves.In ...Excessive pesticide residues on Chinese cabbage will be harmful to people’s health.Therefore,an identification system was designed for qualitative analysis of lambda-cyhalothrin residues on Chinese cabbage leaves.In order to extract discriminant information from mid-infrared(MIR)spectra of Chinese cabbage effectively,fuzzy uncorrelated discriminant vector(FUDV)analysis was proposed by introducing the fuzzy set theory into uncorrelated discriminant vector(UDV)analysis.In this system,the Cary 630 FTIR spectrometer was used to scan four samples of Chinese cabbage with different concentrations of lambda-cyhalothrin.The MIR spectra were preprocessed by standard normal variable(SNV)and Savitzky-Golay smoothing(SG).Next,the high-dimensional MIR spectra were processed for dimension reduction by principal component analysis(PCA).Furthermore,UDV,FUDV,and some other discriminant analysis algorithms were used for feature extraction,respectively.Finally,the K-nearest neighbor(KNN)classifier was employed to classify the data.The experimental results showed that when FUDV was used as the feature extraction algorithm,the identification system reached the maximum classification accuracy of 100%.The results indicated that FUDV combined with MIR spectroscopy was an effective method to identify lambda-cyhalothrin residues on Chinese cabbage.展开更多
文摘Aim To improve the causal diagnosis method presented by Bandekar and propose a new method of finding the root fault order according to the fault possibility by means of numerical calculation. Methods Based on the causal graph, by utilization of fuzzified threshold value and fuzzy discrimination matrix, a kind of fuzzy causal diagnosis method was given and the fault possibility of each elements in the root fault candidate set (RFCS) was obtained. Results and Conclusion The order of each element in the RFCS can be obtained by the fault possibility, which makes the location of fault much easier. The diagnosis speed of this method is quite high, and by means of the fuzzified threshold value and fuzzy discrimination matrix, the result is more robust to noises and bad parameter's choice.
基金The National Natural Science Foundation of China (No.60503023,60872160)the Natural Science Foundation for Universities ofJiangsu Province (No.08KJD520009)the Intramural Research Foundationof Nanjing University of Information Science and Technology(No.Y603)
文摘A novel fuzzy linear discriminant analysis method by the canonical correlation analysis (fuzzy-LDA/CCA)is presented and applied to the facial expression recognition. The fuzzy method is used to evaluate the degree of the class membership to which each training sample belongs. CCA is then used to establish the relationship between each facial image and the corresponding class membership vector, and the class membership vector of a test image is estimated using this relationship. Moreover, the fuzzy-LDA/CCA method is also generalized to deal with nonlinear discriminant analysis problems via kernel method. The performance of the proposed method is demonstrated using real data.
基金This work was supported by the National Natural Science Foundation of China(No.11804263)the Program for Innovative Science and Research Team of Xi’an Technological University.
文摘In order to improve the infrared detection and discrimination ability of the smart munition to the dynamic armor target under the complex background,the multi-line array infrared detection system is established based on the combination of the single unit infrared detector.The surface dimension features of ground armored targets are identified by size calculating solution algorithm.The signal response value and the value of size calculating are identified by the method of fuzzy recognition to make the fuzzy classification judgment for armored target.According to the characteristics of the target signal,a custom threshold de-noising function is proposed to solve the problem of signal preprocessing.The multi-line array infrared detection can complete the scanning detection in a large area in a short time with the characteristics of smart munition in the steady-state scanning stage.The method solves the disadvantages of wide scanning interval and low detection probability of single unit infrared detection.By reducing the scanning interval,the number of random rendezvous in the infrared feature area of the upper surface is increased,the accuracy of the size calculating is guaranteed.The experiments results show that in the fuzzy recognition method,the size calculating is introduced as the feature operator,which can improve the recognition ability of the ground armor target with different shape size.
基金The authors sincerely acknowledge that this work was financially supported by the National Natural Science Foundation of China(Grant No.31471413)the Undergraduate Scientific Research Project of Jiangsu University(Grant No.17A274)the University Natural Science Research Project of Anhui Province(Grant No.KJ2019A1129).
文摘Excessive pesticide residues on Chinese cabbage will be harmful to people’s health.Therefore,an identification system was designed for qualitative analysis of lambda-cyhalothrin residues on Chinese cabbage leaves.In order to extract discriminant information from mid-infrared(MIR)spectra of Chinese cabbage effectively,fuzzy uncorrelated discriminant vector(FUDV)analysis was proposed by introducing the fuzzy set theory into uncorrelated discriminant vector(UDV)analysis.In this system,the Cary 630 FTIR spectrometer was used to scan four samples of Chinese cabbage with different concentrations of lambda-cyhalothrin.The MIR spectra were preprocessed by standard normal variable(SNV)and Savitzky-Golay smoothing(SG).Next,the high-dimensional MIR spectra were processed for dimension reduction by principal component analysis(PCA).Furthermore,UDV,FUDV,and some other discriminant analysis algorithms were used for feature extraction,respectively.Finally,the K-nearest neighbor(KNN)classifier was employed to classify the data.The experimental results showed that when FUDV was used as the feature extraction algorithm,the identification system reached the maximum classification accuracy of 100%.The results indicated that FUDV combined with MIR spectroscopy was an effective method to identify lambda-cyhalothrin residues on Chinese cabbage.