In this work the recently developed fuzzy logic-based adaptive Kalman filter (FL-AKF) is integrated into a neurofuzzy network structure to perform system identification and state estimation of unknown nonlinear systems. This approach, referred to as neurofuzzy adaptive Kalman filter, uses the error signal in the identification process as the measurement noise signal for the FL-AKF in order to estimate the modelling error at the same time in which system identification is performed by the neurofuzzy network. This has a stabilisation effect during the training process when noise is present in the training data. A simulated example is presented to validate the effectiveness of the proposed approach
{"title":"A Neurofuzzy Adaptive Kalman Filter","authors":"P. J. Escamilla-Ambrosio","doi":"10.1109/IS.2006.348485","DOIUrl":"https://doi.org/10.1109/IS.2006.348485","url":null,"abstract":"In this work the recently developed fuzzy logic-based adaptive Kalman filter (FL-AKF) is integrated into a neurofuzzy network structure to perform system identification and state estimation of unknown nonlinear systems. This approach, referred to as neurofuzzy adaptive Kalman filter, uses the error signal in the identification process as the measurement noise signal for the FL-AKF in order to estimate the modelling error at the same time in which system identification is performed by the neurofuzzy network. This has a stabilisation effect during the training process when noise is present in the training data. A simulated example is presented to validate the effectiveness of the proposed approach","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123885576","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}
M. Abbod, J. Catto, D. Linkens, P. Wild, A. Herr, C. Wissmann, C. Pilarsky, A. Hartmann, F. Hamdy
The purpose of this study is to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial intelligence (AI) techniques which provide better predictions than standard traditional statistical methods. The predictive accuracies of neuro-fuzzy modelling (NFM), artificial neural networks (ANN) and traditional logistic regression (LR) methods are compared for the behaviour of bladder cancer. Gene expression profiles of non-invasive and invasive bladder cancer were used to identify potential therapeutic or screening targets in bladder cancer, and to define genetic changes relevant for tumour progression of recurrent papillary bladder cancer (pTa). For all three methods, models were produced to predict the presence and timing of a tumour progression, stage and grade. AI methodology predicted progression with an accuracy ranging up to 100%. This was superior to logistic regression
{"title":"Artificial Intelligence Technique for Gene Expression Profiling of Urinary Bladder Cancer","authors":"M. Abbod, J. Catto, D. Linkens, P. Wild, A. Herr, C. Wissmann, C. Pilarsky, A. Hartmann, F. Hamdy","doi":"10.1109/IS.2006.348495","DOIUrl":"https://doi.org/10.1109/IS.2006.348495","url":null,"abstract":"The purpose of this study is to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial intelligence (AI) techniques which provide better predictions than standard traditional statistical methods. The predictive accuracies of neuro-fuzzy modelling (NFM), artificial neural networks (ANN) and traditional logistic regression (LR) methods are compared for the behaviour of bladder cancer. Gene expression profiles of non-invasive and invasive bladder cancer were used to identify potential therapeutic or screening targets in bladder cancer, and to define genetic changes relevant for tumour progression of recurrent papillary bladder cancer (pTa). For all three methods, models were produced to predict the presence and timing of a tumour progression, stage and grade. AI methodology predicted progression with an accuracy ranging up to 100%. This was superior to logistic regression","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129378920","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}
B. Kolev, K. Atanassov, P. Chountas, I. Petrounias
An integrated data management system is required for representing and managing indicative information from multiple sources describing the state of an enterprise. Current data management systems model enterprises that are crisp. A crisp enterprise is one that is highly quantifiable; relationships are fixed and attributes are atomic valued. The premises for this paper are precise enterprises, data maybe uncertain; multiple sources of information do exist, but uncertainty may be described using different models
{"title":"Merging Probabilistic & Null Values Utilising an Intuitionistic Fuzzy Relational Mediator","authors":"B. Kolev, K. Atanassov, P. Chountas, I. Petrounias","doi":"10.1109/IS.2006.348517","DOIUrl":"https://doi.org/10.1109/IS.2006.348517","url":null,"abstract":"An integrated data management system is required for representing and managing indicative information from multiple sources describing the state of an enterprise. Current data management systems model enterprises that are crisp. A crisp enterprise is one that is highly quantifiable; relationships are fixed and attributes are atomic valued. The premises for this paper are precise enterprises, data maybe uncertain; multiple sources of information do exist, but uncertainty may be described using different models","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115168313","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}
Over recent years order review and release (ORR) has attracted increasing attention in manufacturing research due to its important impact on production performance. By means of effectively controlling the rate of input of jobs into the production system, in fact, the sustainability of feasible and economical production levels can be significantly enhanced. In this context of research the paper proposes a hybrid decision support system (DSS) to address the simultaneous review of multiple incoming orders and, thereby, support better informed acceptance and rejection decisions. The DSS, as developed for this research, relies on the interactive use of simulation and adaptive genetic hybrids, integrating local and global search techniques, to identify the combination of accepted orders that maximizes production performance while reducing the risk of accepting sub-optimal combinations
订单审核与放行(order review and release, ORR)由于其对生产绩效的重要影响，近年来越来越受到制造业研究的关注。事实上，通过有效控制工作投入生产系统的速度，可以显著提高可行和经济生产水平的可持续性。在此研究背景下，本文提出了一种混合决策支持系统(DSS)来解决同时审查多个传入订单的问题，从而支持更明智的接受和拒绝决策。为本研究开发的DSS依赖于模拟和自适应遗传杂交的交互式使用，集成了局部和全局搜索技术，以确定可接受的订单组合，从而最大化生产性能，同时降低接受次优组合的风险
{"title":"Adaptive Genetic Hybrids for Order Review and Release into Production","authors":"A. Orsoni","doi":"10.1109/IS.2006.348521","DOIUrl":"https://doi.org/10.1109/IS.2006.348521","url":null,"abstract":"Over recent years order review and release (ORR) has attracted increasing attention in manufacturing research due to its important impact on production performance. By means of effectively controlling the rate of input of jobs into the production system, in fact, the sustainability of feasible and economical production levels can be significantly enhanced. In this context of research the paper proposes a hybrid decision support system (DSS) to address the simultaneous review of multiple incoming orders and, thereby, support better informed acceptance and rejection decisions. The DSS, as developed for this research, relies on the interactive use of simulation and adaptive genetic hybrids, integrating local and global search techniques, to identify the combination of accepted orders that maximizes production performance while reducing the risk of accepting sub-optimal combinations","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127172791","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 process multitasking driver behavior effectively, an improved driver cognitive behavior modeling method of ACT-R is proposed in this paper. The manual module and visual module of ACT-R are concatenated directly to cope with human subconscious/unconscious behavior. A parallel processing method is proposed to mimic the parallel reactions style of a given cerebral area of human brain's reaction to the physical characteristics of the stimulus. Drive behavior assorting and risk level ranking method are applied to improve the model's executive efficiency. The results of the software simulation show that the improvements of the ACT-R cognitive architecture are efficient and flexible
{"title":"Multitasking Driver Cognitive Behavior Modeling","authors":"Yanfei Liu, Zhaohui Wu","doi":"10.1109/IS.2006.348393","DOIUrl":"https://doi.org/10.1109/IS.2006.348393","url":null,"abstract":"In order to process multitasking driver behavior effectively, an improved driver cognitive behavior modeling method of ACT-R is proposed in this paper. The manual module and visual module of ACT-R are concatenated directly to cope with human subconscious/unconscious behavior. A parallel processing method is proposed to mimic the parallel reactions style of a given cerebral area of human brain's reaction to the physical characteristics of the stimulus. Drive behavior assorting and risk level ranking method are applied to improve the model's executive efficiency. The results of the software simulation show that the improvements of the ACT-R cognitive architecture are efficient and flexible","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127473576","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}
Workflow systems have been widely recognised as a successful way of modelling business processes. The issue of workflow optimisation has received a lot of attention in the literature, but the issue of temporal constraints in this area has received significantly less. At the same time, issues that come from the enterprise, such as actors performing tasks, resources that these tasks utilise, etc. have not been taken into account. This paper proposes a combination of utilisation of enterprise modelling issues and temporal constraints in order to produce a set of rules that aid workflow optimisation and therefore, business process improvement
{"title":"Improving Business Processes Using Enterprise Modelling and Temporal Information","authors":"Dorothy Nan Wang, I. Petrounias","doi":"10.1109/IS.2006.348449","DOIUrl":"https://doi.org/10.1109/IS.2006.348449","url":null,"abstract":"Workflow systems have been widely recognised as a successful way of modelling business processes. The issue of workflow optimisation has received a lot of attention in the literature, but the issue of temporal constraints in this area has received significantly less. At the same time, issues that come from the enterprise, such as actors performing tasks, resources that these tasks utilise, etc. have not been taken into account. This paper proposes a combination of utilisation of enterprise modelling issues and temporal constraints in order to produce a set of rules that aid workflow optimisation and therefore, business process improvement","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123451369","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 the case of complex robotics tasks, pure position control is ineffective since forces appearing during the contacts must also be controlled. However, simultaneous position and force control called hybrid control is then required. Moreover, the non-linear plant dynamics, the complexity of the dynamic parameters determination and computation constraints makes more difficult the synthesis of control laws. In order to satisfy all these constraints, an effective hybrid force/position approach based on artificial neural networks for MIMO systems is proposed. This approach realizes, simultaneously, an identification and control, and it is implemented according to two phases: at first, a neural observer is trained off line on the basis of the data acquired during contact motion, in order to realize a smooth transition from free to contact motion; then, an online learning of the neural controller is implemented using neural observer parameters so that the closed-loop system maintains a good performance. A typical example on which we shall focus is an assembly task. Experimental results on a C5 links parallel robot demonstrate that the robot's skill improves effectively and the force control performances are satisfactory
{"title":"Artificial Neural Network-based Hybrid Force/Position Control of an Assembly Task","authors":"Y. Touati, Y. Amirat, N. Saadia","doi":"10.1109/IS.2006.348486","DOIUrl":"https://doi.org/10.1109/IS.2006.348486","url":null,"abstract":"In the case of complex robotics tasks, pure position control is ineffective since forces appearing during the contacts must also be controlled. However, simultaneous position and force control called hybrid control is then required. Moreover, the non-linear plant dynamics, the complexity of the dynamic parameters determination and computation constraints makes more difficult the synthesis of control laws. In order to satisfy all these constraints, an effective hybrid force/position approach based on artificial neural networks for MIMO systems is proposed. This approach realizes, simultaneously, an identification and control, and it is implemented according to two phases: at first, a neural observer is trained off line on the basis of the data acquired during contact motion, in order to realize a smooth transition from free to contact motion; then, an online learning of the neural controller is implemented using neural observer parameters so that the closed-loop system maintains a good performance. A typical example on which we shall focus is an assembly task. Experimental results on a C5 links parallel robot demonstrate that the robot's skill improves effectively and the force control performances are satisfactory","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116116842","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}
D. Apiletti, Elena Baralis, G. Bruno, T. Cerquitelli
In this paper, we present the IGUANA (individuation of global unsafe anomalies and alarm activation) framework which performs analysis of clinical data to characterize the risk level of a patient and identify dangerous situations. Data mining techniques are exploited to build a model of both normal and unsafe situations, which can be tailored to specific behaviors of a given patient clinical situation. A risk function has been proposed to identify the instantaneous risk of each physiological parameter. The classification phase, performed on-line, assigns a risk label to each measured value. We have developed a prototype of IGUANA in R, an open source environment for statistical analyses and graphical visualization, to validate our approach. Experimental results, performed on 64 records of patients affected by different diseases, show the adaptability and the efficiency of the proposed approach
{"title":"IGUANA: Individuation of Global Unsafe ANomalies and Alarm activation","authors":"D. Apiletti, Elena Baralis, G. Bruno, T. Cerquitelli","doi":"10.1109/IS.2006.348429","DOIUrl":"https://doi.org/10.1109/IS.2006.348429","url":null,"abstract":"In this paper, we present the IGUANA (individuation of global unsafe anomalies and alarm activation) framework which performs analysis of clinical data to characterize the risk level of a patient and identify dangerous situations. Data mining techniques are exploited to build a model of both normal and unsafe situations, which can be tailored to specific behaviors of a given patient clinical situation. A risk function has been proposed to identify the instantaneous risk of each physiological parameter. The classification phase, performed on-line, assigns a risk label to each measured value. We have developed a prototype of IGUANA in R, an open source environment for statistical analyses and graphical visualization, to validate our approach. Experimental results, performed on 64 records of patients affected by different diseases, show the adaptability and the efficiency of the proposed approach","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114415387","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 multi-agent paradigm for building intelligent systems has gradually been accepted by researchers and practitioners in the research field of artificial intelligence. There are also attempts of adapting agents and agent-based systems for creating industrial applications and providing e-services. In this paper, we present an attempt to use agents for constructing an online after-sale services system. The system is decomposed into four major cooperative agents, and in which each agent concentrates on particular aspects in the system and expresses intelligence by using various techniques. The proposed agent-based framework for the system is presented at both the micro-level and the macro-level according to the Gala methodology. UML notations are also used to represent some software design models. As the result of this, agents are implemented into a framework for which exploits case-based reasoning (CBR) technique to fulfil real life on-line services' diagnoses and tasks
{"title":"Towards an Agent-Based Framework for Online After-Sale Services","authors":"Lu Zhang, Frans Coenen, Wei Huang, P. Leng","doi":"10.1109/IS.2006.348456","DOIUrl":"https://doi.org/10.1109/IS.2006.348456","url":null,"abstract":"The multi-agent paradigm for building intelligent systems has gradually been accepted by researchers and practitioners in the research field of artificial intelligence. There are also attempts of adapting agents and agent-based systems for creating industrial applications and providing e-services. In this paper, we present an attempt to use agents for constructing an online after-sale services system. The system is decomposed into four major cooperative agents, and in which each agent concentrates on particular aspects in the system and expresses intelligence by using various techniques. The proposed agent-based framework for the system is presented at both the micro-level and the macro-level according to the Gala methodology. UML notations are also used to represent some software design models. As the result of this, agents are implemented into a framework for which exploits case-based reasoning (CBR) technique to fulfil real life on-line services' diagnoses and tasks","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117295402","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}
M. Blazadonakis, M. Zervakis, M. Kounelakis, E. Biganzoli, Nicola Lama
DNA micro-array analysis allows us to study the expression level of thousands of genes simultaneously on a single experiment. The problem of marker selection has been extensively studied but in this paper we also consider the quality of the selected markers. Thus, we address the problem of selecting a small subset of genes that would be adequate enough to discriminate between the two classes of interest in classification, while preserving self-similar characteristics to allow closed clustering within each class
{"title":"Support Vector Machines and Neural Networks as Marker Selectors for Cancer Gene Analysis","authors":"M. Blazadonakis, M. Zervakis, M. Kounelakis, E. Biganzoli, Nicola Lama","doi":"10.1109/IS.2006.348492","DOIUrl":"https://doi.org/10.1109/IS.2006.348492","url":null,"abstract":"DNA micro-array analysis allows us to study the expression level of thousands of genes simultaneously on a single experiment. The problem of marker selection has been extensively studied but in this paper we also consider the quality of the selected markers. Thus, we address the problem of selecting a small subset of genes that would be adequate enough to discriminate between the two classes of interest in classification, while preserving self-similar characteristics to allow closed clustering within each class","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130402021","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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