Pub Date : 2006-10-16DOI: 10.1109/ISDA.2006.253760
Tie-shan Zhao, Zeng-zhi Li, Ze-Min Wang, Xiaofen Lin
Intrusion detection systems' adaptability and diversity have been researched for long time. With the development of computer immunology, the dynamic clonal selection algorithm is tried to solve the problem. Based on some improved dynamic clonal selection algorithms, an adaptive intrusion detection algorithm is presented in this paper. According to the algorithm, an intrusion detection system is composed of a self-body antigen set, a memorial immunocyte set, a mature immunocyte set and an immature immunocyte set. An immature immunocyte grows into a mature one if it goes through self-tolerance. A mature immunocyte grows into a memorial one if it matches enough non-self-body antigens in limited time and it goes through co-stimulation. A memorial immunocyte doesn't die until it can't go through co-stimulation. Immature immunocytes are generated with clone and hypermutation methods when necessary. The self-body antigen set is renewed during above co-stimulation. Simulation experiments prove that the algorithm have good adaptability and diversity
{"title":"An Adaptive Intrusion Detection Algorithm Based on Improved Dynamic Clonal Selection Algorithms","authors":"Tie-shan Zhao, Zeng-zhi Li, Ze-Min Wang, Xiaofen Lin","doi":"10.1109/ISDA.2006.253760","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253760","url":null,"abstract":"Intrusion detection systems' adaptability and diversity have been researched for long time. With the development of computer immunology, the dynamic clonal selection algorithm is tried to solve the problem. Based on some improved dynamic clonal selection algorithms, an adaptive intrusion detection algorithm is presented in this paper. According to the algorithm, an intrusion detection system is composed of a self-body antigen set, a memorial immunocyte set, a mature immunocyte set and an immature immunocyte set. An immature immunocyte grows into a mature one if it goes through self-tolerance. A mature immunocyte grows into a memorial one if it matches enough non-self-body antigens in limited time and it goes through co-stimulation. A memorial immunocyte doesn't die until it can't go through co-stimulation. Immature immunocytes are generated with clone and hypermutation methods when necessary. The self-body antigen set is renewed during above co-stimulation. Simulation experiments prove that the algorithm have good adaptability and diversity","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128459781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to appraise more accurately the safety conditions of construction sites, evaluation indexes for construction site safety conditions are given. By introducing probability theory and fuzzy group decision methods into construction evaluation, a comprehensive evaluation method based on fuzzy group decision making is put forward. This method applies AHP in determining weight of each expert and uses fuzzy comprehensive evaluation with probability to evaluate the safety conditions of construction sites. Weights and evaluation values of indexes could be reasonably determined when group decision making method is applied. Further, evaluation by means of connecting probability theory and fuzzy evaluation method together is an improvement over the prevalent method of scoring by experts, since safe production conditions could be reflected more objectively and completely
{"title":"A Fuzzy Multicriteria Group Decision Making Method With Probability For Construction Safety Evaluation","authors":"Hongyan Liu, Feng Kong","doi":"10.1109/ISDA.2006.56","DOIUrl":"https://doi.org/10.1109/ISDA.2006.56","url":null,"abstract":"In order to appraise more accurately the safety conditions of construction sites, evaluation indexes for construction site safety conditions are given. By introducing probability theory and fuzzy group decision methods into construction evaluation, a comprehensive evaluation method based on fuzzy group decision making is put forward. This method applies AHP in determining weight of each expert and uses fuzzy comprehensive evaluation with probability to evaluate the safety conditions of construction sites. Weights and evaluation values of indexes could be reasonably determined when group decision making method is applied. Further, evaluation by means of connecting probability theory and fuzzy evaluation method together is an improvement over the prevalent method of scoring by experts, since safe production conditions could be reflected more objectively and completely","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128595422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Selection pressure must be dynamically managed in response to the changing evolutionary process in order to improve the effectiveness and efficiency of genetic programming (GP) systems using tournament selection. Instead of changing the tournament size and/or the population size via an arbitrary function to influence the selection pressure, this paper focuses on designing an automatic selection pressure control approach. In our approach, populations are clustered based on a dynamic program property. Then clusters become tournament candidates. The selection pressure in the tournament selection method is automatically changed during evolution according to the dynamically changing number of tournament candidates. Our approach is compared with the standard GP system (with no selection pressure control) on two problems with different kinds of fitness distributions. The results show that the automatic selection pressure control approach can improve the effectiveness and efficiency of GP systems
{"title":"Automatic Selection Pressure Control in Genetic Programming","authors":"Huayang Xie, Mengjie Zhang, Peter M. Andreae","doi":"10.1109/ISDA.2006.116","DOIUrl":"https://doi.org/10.1109/ISDA.2006.116","url":null,"abstract":"Selection pressure must be dynamically managed in response to the changing evolutionary process in order to improve the effectiveness and efficiency of genetic programming (GP) systems using tournament selection. Instead of changing the tournament size and/or the population size via an arbitrary function to influence the selection pressure, this paper focuses on designing an automatic selection pressure control approach. In our approach, populations are clustered based on a dynamic program property. Then clusters become tournament candidates. The selection pressure in the tournament selection method is automatically changed during evolution according to the dynamically changing number of tournament candidates. Our approach is compared with the standard GP system (with no selection pressure control) on two problems with different kinds of fitness distributions. The results show that the automatic selection pressure control approach can improve the effectiveness and efficiency of GP systems","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129834019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-10-16DOI: 10.1109/ISDA.2006.253733
Ruijie Wang, Junping Du, Wensheng Guo
In this paper we proposed the concepts of multi-agent and data mining technology. We established the design model of Destination Marketing System platform, presented the work flow of Destination Marketing System, and introduced the application of data mining technology on electronic trade platform in detail
{"title":"Realization for Destination Marketing System Platform Based on Data Mining","authors":"Ruijie Wang, Junping Du, Wensheng Guo","doi":"10.1109/ISDA.2006.253733","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253733","url":null,"abstract":"In this paper we proposed the concepts of multi-agent and data mining technology. We established the design model of Destination Marketing System platform, presented the work flow of Destination Marketing System, and introduced the application of data mining technology on electronic trade platform in detail","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125654620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Soft sensor software based on ANN (artificial neural network) using BP or RBF was developed to estimate unmeasured variables such as product quality online. Some important topics including how to determine the delay time, how to simulate the dynamic system were discussed and solved. We applied a 3 layers BP network to identify the delay time of nonlinear system, feedback output variables to input layer, and weight of all the input variables to describe dynamic characteristics of the system. This makes the ANN soft sensor reflect truly both the static and dynamic characteristics of the system and provide more adaptability
{"title":"Delay Time Identification and Dynamic Characteristics Study on ANN Soft Sensor","authors":"D. Du, Chongguang Wu, Xionglin Luo, Xin Zuo","doi":"10.1109/ISDA.2006.131","DOIUrl":"https://doi.org/10.1109/ISDA.2006.131","url":null,"abstract":"Soft sensor software based on ANN (artificial neural network) using BP or RBF was developed to estimate unmeasured variables such as product quality online. Some important topics including how to determine the delay time, how to simulate the dynamic system were discussed and solved. We applied a 3 layers BP network to identify the delay time of nonlinear system, feedback output variables to input layer, and weight of all the input variables to describe dynamic characteristics of the system. This makes the ANN soft sensor reflect truly both the static and dynamic characteristics of the system and provide more adaptability","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"92 33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128885359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Based on the principle of decoupling and neural-network, this paper extends the single-loop single neural control system to multivariable case of the temperature-liquid level two-variable interacting control system in the front box of the pressure net of the papermaking machine. By incorporating static feed-forward decoupling compensation, a learning-type decentralize multivariable control system has been proposed. With a parameter tuning algorithm, the nonlinear single neural controller (SNC) in each loop is able to control a changing process by merely observing the process output error in the loop. The only a priori plant information is the process steady state gain, which can be easily obtained from open-loop test. Thus, good regulating performance is guaranteed in the initial control stage, even the controlled object varies later. Simulation results show that this strategy is effective and practicable
{"title":"On Multivariable Neural Network Decoupling Control System","authors":"Weimin Yang, Dongmei Lv","doi":"10.1109/ISDA.2006.33","DOIUrl":"https://doi.org/10.1109/ISDA.2006.33","url":null,"abstract":"Based on the principle of decoupling and neural-network, this paper extends the single-loop single neural control system to multivariable case of the temperature-liquid level two-variable interacting control system in the front box of the pressure net of the papermaking machine. By incorporating static feed-forward decoupling compensation, a learning-type decentralize multivariable control system has been proposed. With a parameter tuning algorithm, the nonlinear single neural controller (SNC) in each loop is able to control a changing process by merely observing the process output error in the loop. The only a priori plant information is the process steady state gain, which can be easily obtained from open-loop test. Thus, good regulating performance is guaranteed in the initial control stage, even the controlled object varies later. Simulation results show that this strategy is effective and practicable","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132898397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents the application of fuzzy c means based radial basis function (RBF) network model to short term load forecasting problem. Traditional learning process for BP network is a nonlinear optimizing process, thus resulting in slow convergence speed, local minima. While the ability of approaching nonlinear function and convergence speed for RBF is superior to BP network. Before training network, suitable historical data were selected as training set through calculating difference degree function. This can make the training set representative, thus reduce training time. The proposed model has been implemented on real data: inputs to RFB are historical load value, weather, day and temperature information, and the output is the load forecast for the given hour. This model can effectively improve the speed of convergence. Using the presented model, the better forecasting accuracy and learning potency can be achieved
{"title":"Short-term Load Forecasting Model Using Fuzzy C Means Based Radial Basis Function Network","authors":"Youchan Zhu, Yujun He","doi":"10.1109/ISDA.2006.235","DOIUrl":"https://doi.org/10.1109/ISDA.2006.235","url":null,"abstract":"This paper presents the application of fuzzy c means based radial basis function (RBF) network model to short term load forecasting problem. Traditional learning process for BP network is a nonlinear optimizing process, thus resulting in slow convergence speed, local minima. While the ability of approaching nonlinear function and convergence speed for RBF is superior to BP network. Before training network, suitable historical data were selected as training set through calculating difference degree function. This can make the training set representative, thus reduce training time. The proposed model has been implemented on real data: inputs to RFB are historical load value, weather, day and temperature information, and the output is the load forecast for the given hour. This model can effectively improve the speed of convergence. Using the presented model, the better forecasting accuracy and learning potency can be achieved","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130470016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-10-16DOI: 10.1109/ISDA.2006.253804
Fengli Fan, Zhao Tong, Shulin Sui, Changhe Du
In this paper, in order to design control scheme to mitigate the effects of unknown hysteresis, a class of novel hysteresis models are proposed. We superpose a finite of many different deadband width backlash models, which represented as a dynamics to mimic hysteresis in actuator. With the model proposed, a single hidden layer neural network (NN-based) adaptive control scheme for nonlinear systems with unknown hysteresis nonlinearity is developed. The control scheme adopts the design method of pseudo-control. For the nonlinear dynamic systems, with time-varying external disturbance and strong nonlinearity and large uncertainty of unknown hysteresis, which output is not available, we adopt Hinfin optimal control techniques. Our result indicates that arbitrarily small attenuation level can be achieved via the proposed adaptive neural networks control algorithm if a weighting factor of control variable is adequately chosen. The effectiveness of the proposed control scheme is illustrated through simulation
{"title":"Adaptive Neural Network Control for Nonlinear Systems with Unknown Hysteresis via Hinfty Approaches","authors":"Fengli Fan, Zhao Tong, Shulin Sui, Changhe Du","doi":"10.1109/ISDA.2006.253804","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253804","url":null,"abstract":"In this paper, in order to design control scheme to mitigate the effects of unknown hysteresis, a class of novel hysteresis models are proposed. We superpose a finite of many different deadband width backlash models, which represented as a dynamics to mimic hysteresis in actuator. With the model proposed, a single hidden layer neural network (NN-based) adaptive control scheme for nonlinear systems with unknown hysteresis nonlinearity is developed. The control scheme adopts the design method of pseudo-control. For the nonlinear dynamic systems, with time-varying external disturbance and strong nonlinearity and large uncertainty of unknown hysteresis, which output is not available, we adopt Hinfin optimal control techniques. Our result indicates that arbitrarily small attenuation level can be achieved via the proposed adaptive neural networks control algorithm if a weighting factor of control variable is adequately chosen. The effectiveness of the proposed control scheme is illustrated through simulation","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127918411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Equal set is the most important concept in rough set. In classic rough set model, the equality is strong, must be very precise. But strong equality cause inapplicable due to data noise. Variable precision rough set model solve the data noise by introducing an error-tolerated factor. But there are no weighted factors in knowledge system. Especially, after data cleaning, rules those have same form will be unite to one rule. But objects have different importance is more close to actually application. In this paper, weighted rough set (WRS) model is provided. WRS is based on variable precision rough set (VPRS) model. This model not only considers the noise tolerant capability, but also considers the objects' importance. In weighted rough set model, some basic concepts are redefined. Also, reduction definition is provided. At last, from the experiments, weighted rough set model's characters are got
{"title":"Weighted Rough Set Model","authors":"Tinghuai Ma, Meili Tang","doi":"10.1109/ISDA.2006.280","DOIUrl":"https://doi.org/10.1109/ISDA.2006.280","url":null,"abstract":"Equal set is the most important concept in rough set. In classic rough set model, the equality is strong, must be very precise. But strong equality cause inapplicable due to data noise. Variable precision rough set model solve the data noise by introducing an error-tolerated factor. But there are no weighted factors in knowledge system. Especially, after data cleaning, rules those have same form will be unite to one rule. But objects have different importance is more close to actually application. In this paper, weighted rough set (WRS) model is provided. WRS is based on variable precision rough set (VPRS) model. This model not only considers the noise tolerant capability, but also considers the objects' importance. In weighted rough set model, some basic concepts are redefined. Also, reduction definition is provided. At last, from the experiments, weighted rough set model's characters are got","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129177176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The problem considered in this paper is that of selecting, from a set of proposals or a subset of projects to be undertaken. It is influenced by a large number of factors, and many times it is hard to measure them in numbers or an objectively way. This paper addresses this by presenting a method for identifying and assessing key project characteristics, which are crucial for a technology project's success. First, this paper builds a new set of indicators of technology project evaluation after analysing the process of technology project evaluation. Secondly, this paper introduces an aggregation operator to deal with linguistic and subjective information. The method consists of a number of well defined steps, which are described in detail. Finally, an example shows that the proposed method using subjective and linguistic factors is useful and it provides an understanding way for the decision maker
{"title":"An Approach of Technology Project Evaluation with Linguistic and Subjective Information","authors":"Xiu-Li Pang, Yu-Qiang Feng","doi":"10.1109/ISDA.2006.90","DOIUrl":"https://doi.org/10.1109/ISDA.2006.90","url":null,"abstract":"The problem considered in this paper is that of selecting, from a set of proposals or a subset of projects to be undertaken. It is influenced by a large number of factors, and many times it is hard to measure them in numbers or an objectively way. This paper addresses this by presenting a method for identifying and assessing key project characteristics, which are crucial for a technology project's success. First, this paper builds a new set of indicators of technology project evaluation after analysing the process of technology project evaluation. Secondly, this paper introduces an aggregation operator to deal with linguistic and subjective information. The method consists of a number of well defined steps, which are described in detail. Finally, an example shows that the proposed method using subjective and linguistic factors is useful and it provides an understanding way for the decision maker","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125358396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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