Point-wise negative selection algorithms,which generate their detector sets based on point of self data,have lower training efficiency and detection rate.To solve this problem,a self region based real-valued negative ...Point-wise negative selection algorithms,which generate their detector sets based on point of self data,have lower training efficiency and detection rate.To solve this problem,a self region based real-valued negative selection algorithm is presented.In this new approach,the continuous self region is defined by the collection of self data,the partial training takes place at the training stage according to both the radius of self region and the cosine distance between gravity of the self region and detector candidate,and variable detectors in the self region are deployed.The algorithm is tested using the triangle shape of self region in the 2-D complement space and KDD CUP 1999 data set.Results show that,more information can be provided when the training self points are used together as a whole,and compared with the point-wise negative selection algorithm,the new approach can improve the training efficiency of system and the detection rate significantly.展开更多
With the Industry 4.0 era coming, modern chemical plants will be gradually transformed into smart factories, which sets higher requirements for fault detection and diagnosis(FDD) to enhance operation safety intelligen...With the Industry 4.0 era coming, modern chemical plants will be gradually transformed into smart factories, which sets higher requirements for fault detection and diagnosis(FDD) to enhance operation safety intelligence. In a typical chemical process, there are hundreds of process variables. Feature selection is a key to the efficiency and effectiveness of FDD. Even though artificial immune system has advantages in adaptation and independency on a large number of fault samples, antibody library construction used to be based on experience. It is not only time consuming, but also lack of scientific foundation in fault feature selection, which may deteriorate the FDD performance of the AIS. In this paper, a fault antibody feature selection optimization(FAFSO) algorithm is proposed based on genetic algorithm to optimize the fault antibody features and the antibody libraries' thresholds simultaneously. The performance of the proposed FAFSO algorithms is illustrated through the Tennessee Eastman benchmark problem.展开更多
Accordion-shaped traps are widely used in China to catch the Asian paddle crab C harybdis japonica but traps of conventional design often catch juvenile crabs. A new type of accordion-shaped trap with an escape vent(L...Accordion-shaped traps are widely used in China to catch the Asian paddle crab C harybdis japonica but traps of conventional design often catch juvenile crabs. A new type of accordion-shaped trap with an escape vent(L×W=4.3 cm×3.0 cm) was designed and a comparative study between the newly designed and conventional traps was performed in the artifi cial reef area of Zhuwang, Laizhou Bay, China from June to August 2012. The mean catch per unit effort(CPUE) of undersized crabs was signifi cantly lower in the vented traps than in the conventional traps(paired t-test, n =30, P <0.001), while the CPUE of marketable crabs was signifi cantly higher in the vented traps(paired t-test, n =30, P <0.001). The mean size of crabs(carapace length) caught in the vented traps was signifi cantly larger than in conventional traps(paired t-test, n =29, P <0.001). The ratio of undersized crabs was 35.05%±2.57% in conventional traps and 12.53%±0.69% in vented traps(signifi cantly lower, paired t-test, n =29, P <0.001). Therefore, a 4.3 cm×3.0 cm escape vent was considered appropriate for C. japonica fi shing in the artifi cial reef area. This fi nding will assist the development of more sustainable and effi cient crab fi shing methods using accordion-shaped traps.展开更多
Clothing manufacturers＇ direct investment and joint ventures in developing regions have seen to grow rapidly in the past few decades. Non-optimized selection can contribute to adverse effects affecting the performanc...Clothing manufacturers＇ direct investment and joint ventures in developing regions have seen to grow rapidly in the past few decades. Non-optimized selection can contribute to adverse effects affecting the performance of the plants on aspects of productivity, manufacturing and logistics cost. Selection of proper plant location is thus crucial. The conventional approaches to sites location are based on the factors and their weights. However, determining the weight of each factor is very difficult and time consuming. While the situation is changed, all the work must be redone again. This study aims to develop a decision-making system on clothing plant location for Hoog Kong clothing manufacturer. The proposed system utilizes artificial neural network to study the relationship between the factors and the suitability index of candidate sites. Firstly, the factors are stratified using the fuzzy analytical hierarchy process （FAHP） by review the related references and interviewing the experts. Secondly, the corresponding data are collected from the experts by questionnaire and the related government publication. Finally, the feedforward neural network with error backpropagation（EBP） learning algorithm is trained and applied to make decision. The results show that the proposed system performs well and has the characteristic of adaptability and plasticity.展开更多
A new matting algorithm based on color distance and differential distance is proposed to deal with the problem that many matting methods perform poorly with complex natural images.The proposed method combines local sa...A new matting algorithm based on color distance and differential distance is proposed to deal with the problem that many matting methods perform poorly with complex natural images.The proposed method combines local sampling with global sampling to select foreground and background pairs for unknown pixels and then a new cost function is constructed based on color distance and differential distance to further optimize the selected sample pairs.Finally,a quadratic objective function is used based on matte Laplacian coming from KNN matting which is added with texture feature.Through experiments on various test images,it is confirmed that the results obtained by the proposed method are more accurate than those obtained by traditional methods.The four-error-metrics comparison on benchmark dataset among several algorithms also proves the effectiveness of the proposed method.展开更多
A real-valued negative selection algorithm with good mathematical foundation is presented to solve some of the drawbacks of previous approach. Specifically, it can produce a good estimate of the optimal number of dete...A real-valued negative selection algorithm with good mathematical foundation is presented to solve some of the drawbacks of previous approach. Specifically, it can produce a good estimate of the optimal number of detectors needed to cover the non-self space, and the maximization of the non-self coverage is done through an optimization algorithm with proven convergence properties. Experiments are performed to validate the assumptions made while designing the algorithm and to evaluate its performance.展开更多
Since the beginning of computer games era, artificial intelligence (AI) has been a standard feature of games. The current emphasis in computer game AI is improving the quality of opponent AI. Our research question rea...Since the beginning of computer games era, artificial intelligence (AI) has been a standard feature of games. The current emphasis in computer game AI is improving the quality of opponent AI. Our research question reads: How can unsupervised online learning be incorporated in Computer Role Playing Game(CRPG) to improve the strategy of the opponent AI? Our goal is to use online evolutionary learning to design strategies that can defeat the opponent. So we apply a novel technique called dynamic scripting that realizes online adaptation of scripted opponent AI and report on experiments performed in a simulated CRPG to assess the adaptive performance obtained with the technique.展开更多
Some researchers in mechanical engineering have developed systems for the design of gear transmission boxes, but almost no calculation methods exist for widespread synthesis. In this article, we outline methods for au...Some researchers in mechanical engineering have developed systems for the design of gear transmission boxes, but almost no calculation methods exist for widespread synthesis. In this article, we outline methods for automatic determination of toothed helical gear trains and the selection criteria for the optimal choice of gear trains. In this work two methods were applied. As first design to use an expert system for the design and then optimize the design that is why we used Kappa PC and Catia for CAD.展开更多
基金Sponsored by the National Natural Science Foundation of China (Grant No. 60671049)the Subject Chief Foundation of Harbin (Grant No.2003AFXXJ013)+1 种基金the Education Department Research Foundation of Heilongjiang Province(Grant No. 10541044, 1151G012)the Postdoctor Foundation of Heilongjiang Province(Grant No.LBH-Z05092)
文摘Point-wise negative selection algorithms,which generate their detector sets based on point of self data,have lower training efficiency and detection rate.To solve this problem,a self region based real-valued negative selection algorithm is presented.In this new approach,the continuous self region is defined by the collection of self data,the partial training takes place at the training stage according to both the radius of self region and the cosine distance between gravity of the self region and detector candidate,and variable detectors in the self region are deployed.The algorithm is tested using the triangle shape of self region in the 2-D complement space and KDD CUP 1999 data set.Results show that,more information can be provided when the training self points are used together as a whole,and compared with the point-wise negative selection algorithm,the new approach can improve the training efficiency of system and the detection rate significantly.
基金Supported by the National Natural Science Foundation of China(61433001)
文摘With the Industry 4.0 era coming, modern chemical plants will be gradually transformed into smart factories, which sets higher requirements for fault detection and diagnosis(FDD) to enhance operation safety intelligence. In a typical chemical process, there are hundreds of process variables. Feature selection is a key to the efficiency and effectiveness of FDD. Even though artificial immune system has advantages in adaptation and independency on a large number of fault samples, antibody library construction used to be based on experience. It is not only time consuming, but also lack of scientific foundation in fault feature selection, which may deteriorate the FDD performance of the AIS. In this paper, a fault antibody feature selection optimization(FAFSO) algorithm is proposed based on genetic algorithm to optimize the fault antibody features and the antibody libraries' thresholds simultaneously. The performance of the proposed FAFSO algorithms is illustrated through the Tennessee Eastman benchmark problem.
基金Supported by the Public Science and Technology Research Funds Projects of Ocean(Nos.201305043,201405010)the National Natural Science Foundation of China(No.41006075)
文摘Accordion-shaped traps are widely used in China to catch the Asian paddle crab C harybdis japonica but traps of conventional design often catch juvenile crabs. A new type of accordion-shaped trap with an escape vent(L×W=4.3 cm×3.0 cm) was designed and a comparative study between the newly designed and conventional traps was performed in the artifi cial reef area of Zhuwang, Laizhou Bay, China from June to August 2012. The mean catch per unit effort(CPUE) of undersized crabs was signifi cantly lower in the vented traps than in the conventional traps(paired t-test, n =30, P <0.001), while the CPUE of marketable crabs was signifi cantly higher in the vented traps(paired t-test, n =30, P <0.001). The mean size of crabs(carapace length) caught in the vented traps was signifi cantly larger than in conventional traps(paired t-test, n =29, P <0.001). The ratio of undersized crabs was 35.05%±2.57% in conventional traps and 12.53%±0.69% in vented traps(signifi cantly lower, paired t-test, n =29, P <0.001). Therefore, a 4.3 cm×3.0 cm escape vent was considered appropriate for C. japonica fi shing in the artifi cial reef area. This fi nding will assist the development of more sustainable and effi cient crab fi shing methods using accordion-shaped traps.
文摘Clothing manufacturers＇ direct investment and joint ventures in developing regions have seen to grow rapidly in the past few decades. Non-optimized selection can contribute to adverse effects affecting the performance of the plants on aspects of productivity, manufacturing and logistics cost. Selection of proper plant location is thus crucial. The conventional approaches to sites location are based on the factors and their weights. However, determining the weight of each factor is very difficult and time consuming. While the situation is changed, all the work must be redone again. This study aims to develop a decision-making system on clothing plant location for Hoog Kong clothing manufacturer. The proposed system utilizes artificial neural network to study the relationship between the factors and the suitability index of candidate sites. Firstly, the factors are stratified using the fuzzy analytical hierarchy process （FAHP） by review the related references and interviewing the experts. Secondly, the corresponding data are collected from the experts by questionnaire and the related government publication. Finally, the feedforward neural network with error backpropagation（EBP） learning algorithm is trained and applied to make decision. The results show that the proposed system performs well and has the characteristic of adaptability and plasticity.
基金Supported by the National Natural Science Foundation of China(No.61133009,U1304616)
文摘A new matting algorithm based on color distance and differential distance is proposed to deal with the problem that many matting methods perform poorly with complex natural images.The proposed method combines local sampling with global sampling to select foreground and background pairs for unknown pixels and then a new cost function is constructed based on color distance and differential distance to further optimize the selected sample pairs.Finally,a quadratic objective function is used based on matte Laplacian coming from KNN matting which is added with texture feature.Through experiments on various test images,it is confirmed that the results obtained by the proposed method are more accurate than those obtained by traditional methods.The four-error-metrics comparison on benchmark dataset among several algorithms also proves the effectiveness of the proposed method.
基金Sponsored by the National Natural Science Foundation of China ( Grant No. 60671049 ), the Subject Chief Foundation of Harbin ( Grant No.2003AFXXJ013), the Education Department Research Foundation of Heilongjiang Province(Grant No.10541044,1151G012) and the Postdoctor Founda-tion of Heilongjiang(Grant No.LBH-Z05092).
文摘A real-valued negative selection algorithm with good mathematical foundation is presented to solve some of the drawbacks of previous approach. Specifically, it can produce a good estimate of the optimal number of detectors needed to cover the non-self space, and the maximization of the non-self coverage is done through an optimization algorithm with proven convergence properties. Experiments are performed to validate the assumptions made while designing the algorithm and to evaluate its performance.
文摘Since the beginning of computer games era, artificial intelligence (AI) has been a standard feature of games. The current emphasis in computer game AI is improving the quality of opponent AI. Our research question reads: How can unsupervised online learning be incorporated in Computer Role Playing Game(CRPG) to improve the strategy of the opponent AI? Our goal is to use online evolutionary learning to design strategies that can defeat the opponent. So we apply a novel technique called dynamic scripting that realizes online adaptation of scripted opponent AI and report on experiments performed in a simulated CRPG to assess the adaptive performance obtained with the technique.
文摘Some researchers in mechanical engineering have developed systems for the design of gear transmission boxes, but almost no calculation methods exist for widespread synthesis. In this article, we outline methods for automatic determination of toothed helical gear trains and the selection criteria for the optimal choice of gear trains. In this work two methods were applied. As first design to use an expert system for the design and then optimize the design that is why we used Kappa PC and Catia for CAD.
