Pub Date : 2003-02-01DOI: 10.1109/TSMCC.2003.809362
A. Sage
For more than a quarter of a century, Madan G. Singh taught and accomplished seminal research on approaches to better control, manage, and understand complexity in systems. This interdisciplinary work has covered the intersections of the areas of control engineering, systems engineering, applied mathematics, management science, and computer science. His work has been remarkable at both a theoretical level, as well as at a practical level. Indeed, over the years, his practical work has led to new insights which have driven the theoretical developments. He has examined complexity in human-made systems, in managerial decision making, in marketing, and in production planning and scheduling. He has taken full advantage of contemporary developments in computing technology and in organizational science. He was, in a great many respects, a truly excellent exemplar of the modern academic, with highly tuned entrepreneurial skills integrated with major research skills. His career reflects well the contemporary changing character of academia that is now simultaneously home to ivory tower research, pragmatic market-driven research and associated product and service development. The purpose of this commemorative paper is to describe the evolution of his academic, research, scholarship, professional service, and enterprise efforts over the last two and a half decades.
在超过四分之一个世纪的时间里，Madan G. Singh教授并完成了关于更好地控制、管理和理解系统复杂性的方法的开创性研究。这项跨学科的工作涵盖了控制工程、系统工程、应用数学、管理科学和计算机科学等领域的交叉点。他的工作无论在理论层面还是在实践层面都是卓越的。事实上，多年来，他的实际工作带来了新的见解，推动了理论的发展。他研究了人造系统、管理决策、市场营销以及生产计划和调度的复杂性。他充分利用了当代计算机技术和组织科学的发展。在很多方面，他都是现代学者的真正优秀典范，他的创业技能与主要的研究技能相结合。他的职业生涯很好地反映了当代学术界不断变化的特征，现在学术界同时拥有象牙塔研究、务实的市场驱动研究以及相关的产品和服务开发。这篇纪念论文的目的是描述他在过去25年的学术、研究、学术、专业服务和企业努力的演变。
{"title":"Madan G. Singh (1946-2002): distinguished academic, scholar, and entrepreneur","authors":"A. Sage","doi":"10.1109/TSMCC.2003.809362","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809362","url":null,"abstract":"For more than a quarter of a century, Madan G. Singh taught and accomplished seminal research on approaches to better control, manage, and understand complexity in systems. This interdisciplinary work has covered the intersections of the areas of control engineering, systems engineering, applied mathematics, management science, and computer science. His work has been remarkable at both a theoretical level, as well as at a practical level. Indeed, over the years, his practical work has led to new insights which have driven the theoretical developments. He has examined complexity in human-made systems, in managerial decision making, in marketing, and in production planning and scheduling. He has taken full advantage of contemporary developments in computing technology and in organizational science. He was, in a great many respects, a truly excellent exemplar of the modern academic, with highly tuned entrepreneurial skills integrated with major research skills. His career reflects well the contemporary changing character of academia that is now simultaneously home to ivory tower research, pragmatic market-driven research and associated product and service development. The purpose of this commemorative paper is to describe the evolution of his academic, research, scholarship, professional service, and enterprise efforts over the last two and a half decades.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"12 1","pages":"7-12"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74991418","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809356
K. Hipel, N. Okada, K. Fukuyama
Two international exchange programs in engineering between universities in Japan and Canada, are described in order to explain the significant benefits gained by the undergraduate and graduate students, as well as the academic staff who participate, and to highlight key principles generally followed in the design and execution of exchange programs. One notable and successful engineering exchange program is between the University of Waterloo, located in Southern Ontario, Canada, and Tottori University in Japan, while the other is between the University of Waterloo and Kyoto University in Japan. Both of these programs include foreign students taking courses for credit or audit at the host university, and, for the case of graduate students, also receiving guidance in their research. Moreover, upon completion of one academic semester in Japan, all of the undergraduate Waterloo students studying at Tottori University are employed in Japanese industry for three to four months before returning to Canada. Of paramount importance to the education of the participating undergraduate and graduate students is the opportunity to learn, by first-hand experience, the language and culture of a foreign country. In fact, one of the key findings of a survey completed by Canadian and Japanese students who took part in the exchange programs, is that living in a different culture greatly enhanced their own personal development. The addition of this international perspective to a solid education in engineering opens many doors of opportunity for exchange program alumni, who are well prepared to fully participate in the global marketplace of the 21st century, and to assist society in responsibly reaching an equitable and sustainable future.
{"title":"The internationalization of engineering education: a tale of two countries","authors":"K. Hipel, N. Okada, K. Fukuyama","doi":"10.1109/TSMCC.2003.809356","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809356","url":null,"abstract":"Two international exchange programs in engineering between universities in Japan and Canada, are described in order to explain the significant benefits gained by the undergraduate and graduate students, as well as the academic staff who participate, and to highlight key principles generally followed in the design and execution of exchange programs. One notable and successful engineering exchange program is between the University of Waterloo, located in Southern Ontario, Canada, and Tottori University in Japan, while the other is between the University of Waterloo and Kyoto University in Japan. Both of these programs include foreign students taking courses for credit or audit at the host university, and, for the case of graduate students, also receiving guidance in their research. Moreover, upon completion of one academic semester in Japan, all of the undergraduate Waterloo students studying at Tottori University are employed in Japanese industry for three to four months before returning to Canada. Of paramount importance to the education of the participating undergraduate and graduate students is the opportunity to learn, by first-hand experience, the language and culture of a foreign country. In fact, one of the key findings of a survey completed by Canadian and Japanese students who took part in the exchange programs, is that living in a different culture greatly enhanced their own personal development. The addition of this international perspective to a solid education in engineering opens many doors of opportunity for exchange program alumni, who are well prepared to fully participate in the global marketplace of the 21st century, and to assist society in responsibly reaching an equitable and sustainable future.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"30 1","pages":"137-148"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81760364","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809354
L. Mikhailov, M. Singh
In this paper we propose a fuzzy extension of the analytic network process (ANP) that uses uncertain human preferences as input information in the decision-making process. Instead of the classical Eigenvector prioritization method, employed in the prioritization stage of the ANP, a new fuzzy preference programming method, which obtains crisp priorities from inconsistent interval and fuzzy judgments is applied. The resulting fuzzy ANP enhances the potential of the ANP for dealing with imprecise and uncertain human comparison judgments. It allows for multiple representations of uncertain human preferences, as crisp, interval, and fuzzy judgments and can find a solution from incomplete sets of pairwise comparisons. An important feature of the proposed method is that it measures the inconsistency of the uncertain human preferences by an appropriate consistency index. A prototype decision support system realizing the proposed method is developed, and its performance is illustrated by examples.
{"title":"Fuzzy analytic network process and its application to the development of decision support systems","authors":"L. Mikhailov, M. Singh","doi":"10.1109/TSMCC.2003.809354","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809354","url":null,"abstract":"In this paper we propose a fuzzy extension of the analytic network process (ANP) that uses uncertain human preferences as input information in the decision-making process. Instead of the classical Eigenvector prioritization method, employed in the prioritization stage of the ANP, a new fuzzy preference programming method, which obtains crisp priorities from inconsistent interval and fuzzy judgments is applied. The resulting fuzzy ANP enhances the potential of the ANP for dealing with imprecise and uncertain human comparison judgments. It allows for multiple representations of uncertain human preferences, as crisp, interval, and fuzzy judgments and can find a solution from incomplete sets of pairwise comparisons. An important feature of the proposed method is that it measures the inconsistency of the uncertain human preferences by an appropriate consistency index. A prototype decision support system realizing the proposed method is developed, and its performance is illustrated by examples.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"80 1","pages":"33-41"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87096616","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809360
L. Fang, K. Hipel, D. Kilgour, Xiaoyong Peng
For pt.I see ibid., p.42-55 (2003). The development of a comprehensive decision support system, GMCR II, for the systematic study of real-world interactive decision problems is presented. The companion paper (Part I), discusses how GMCR II elicits, stores, and manages conflict models; here (Part II), the focus is on GMCR IIs analysis and output interpretation subsystems. Specifically, this paper describes the powerful and efficient analysis engine contained in GMCR II, its informative output presentation and interpretation facilities, and a number of follow-up analyses. Furthermore, an illustrative case study is used to demonstrate how GMCR II can be conveniently applied in practice.
{"title":"A decision support system for interactive decision making - Part II: analysis and output interpretation","authors":"L. Fang, K. Hipel, D. Kilgour, Xiaoyong Peng","doi":"10.1109/TSMCC.2003.809360","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809360","url":null,"abstract":"For pt.I see ibid., p.42-55 (2003). The development of a comprehensive decision support system, GMCR II, for the systematic study of real-world interactive decision problems is presented. The companion paper (Part I), discusses how GMCR II elicits, stores, and manages conflict models; here (Part II), the focus is on GMCR IIs analysis and output interpretation subsystems. Specifically, this paper describes the powerful and efficient analysis engine contained in GMCR II, its informative output presentation and interpretation facilities, and a number of follow-up analyses. Furthermore, an illustrative case study is used to demonstrate how GMCR II can be conveniently applied in practice.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"42 1","pages":"56-66"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86450963","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809869
A. Wong, Yang Wang
Decision support nowadays is more and more targeted to large scale complicated systems and domains. The success of a decision support system relies mainly on its capability of processing large amounts of data and efficiently extracting useful knowledge from the data, especially knowledge which is previously unknown to the decision makers. With a large scale system, traditional knowledge acquisition models become inefficient and/or more biased, due to the subjectivity of the experts or the pre-assumptions of certain ideas or algorithmic procedures. Today, with the rapid development of computer technologies, the capability of collecting data has been greatly advanced. Data becomes the most valuable resource for an organization. We present a fundamental framework toward intelligent decision support by analyzing a large amount of mixed-mode data (data with a mixture of continuous and categorical values) in order to bridge the subjectivity and objectivity of a decision support process. By considering significant associations of artifacts (events) inherent in the data as patterns, we define patterns as statistically significant associations among feature values represented by joint events or hypercells in the feature space. We then present an algorithm which automatically discovers statistically significant hypercells (patterns) based on: 1) a residual analysis, which tests the significance of the deviation when the occurrence of a hypercell differs from its expectation, and 2) an optimization formulation to enable recursive discovery. By discovering patterns from data sets based on such an objective measure, the nature of the problem domain will be revealed. The patterns can then be applied to solve specific problems as being interpreted or inferred with.
{"title":"Pattern discovery: a data driven approach to decision support","authors":"A. Wong, Yang Wang","doi":"10.1109/TSMCC.2003.809869","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809869","url":null,"abstract":"Decision support nowadays is more and more targeted to large scale complicated systems and domains. The success of a decision support system relies mainly on its capability of processing large amounts of data and efficiently extracting useful knowledge from the data, especially knowledge which is previously unknown to the decision makers. With a large scale system, traditional knowledge acquisition models become inefficient and/or more biased, due to the subjectivity of the experts or the pre-assumptions of certain ideas or algorithmic procedures. Today, with the rapid development of computer technologies, the capability of collecting data has been greatly advanced. Data becomes the most valuable resource for an organization. We present a fundamental framework toward intelligent decision support by analyzing a large amount of mixed-mode data (data with a mixture of continuous and categorical values) in order to bridge the subjectivity and objectivity of a decision support process. By considering significant associations of artifacts (events) inherent in the data as patterns, we define patterns as statistically significant associations among feature values represented by joint events or hypercells in the feature space. We then present an algorithm which automatically discovers statistically significant hypercells (patterns) based on: 1) a residual analysis, which tests the significance of the deviation when the occurrence of a hypercell differs from its expectation, and 2) an optimization formulation to enable recursive discovery. By discovering patterns from data sets based on such an objective measure, the nature of the problem domain will be revealed. The patterns can then be applied to solve specific problems as being interpreted or inferred with.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"36 1","pages":"114-124"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82622090","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809866
A. Meystel
Decision support systems gain better performance and higher accuracy by the virtue of building multiresolutional (multigranular, multiscale) representation, and employing multiscale behavior generation subsystem (planning and control). The latter are equipped by devices for unsupervised learning that adjust their functioning to the results of self-identification. We demonstrate that planning and learning are joint processes. The author's intention is to emphasize that the concepts of multiresolutional representation (MR) and multiresolutional decision support (MR-DSS) probably have in common a general significance that crosses the boundaries of particular domains of applications and disciplines. The paper explores this phenomenon. The ubiquity of a principle that somehow persistently delivers benefits to many areas of knowledge and technology seems to be more important than a habit to follow the pigeonhole principle of paper presentation.
{"title":"Multiresolutional hierarchical decision support systems","authors":"A. Meystel","doi":"10.1109/TSMCC.2003.809866","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809866","url":null,"abstract":"Decision support systems gain better performance and higher accuracy by the virtue of building multiresolutional (multigranular, multiscale) representation, and employing multiscale behavior generation subsystem (planning and control). The latter are equipped by devices for unsupervised learning that adjust their functioning to the results of self-identification. We demonstrate that planning and learning are joint processes. The author's intention is to emphasize that the concepts of multiresolutional representation (MR) and multiresolutional decision support (MR-DSS) probably have in common a general significance that crosses the boundaries of particular domains of applications and disciplines. The paper explores this phenomenon. The ubiquity of a principle that somehow persistently delivers benefits to many areas of knowledge and technology seems to be more important than a habit to follow the pigeonhole principle of paper presentation.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"5 1","pages":"86-101"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85003766","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 : 2003-01-01DOI: 10.1109/TSMCC.2003.813148
Xiaobu Yuan, Simon X. Yang
This paper investigates the introduction of biologically inspired intelligence into virtual assembly. It develops an approach to assist product engineers making assembly-related manufacturing decisions without actually realizing the physical products. This approach extracts the knowledge of mechanical assembly by allowing human operators to perform assembly operations directly in the virtual environment. The incorporation of a biologically inspired neural network into an interactive assembly planner further leads to the improvement of flexible product manufacturing, i.e., automatically producing alternative assembly sequences with robot-level instructions for evaluation and optimization. Complexity analysis and simulation study demonstrate the effectiveness and efficiency of this approach.
{"title":"Virtual assembly with biologically inspired intelligence","authors":"Xiaobu Yuan, Simon X. Yang","doi":"10.1109/TSMCC.2003.813148","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.813148","url":null,"abstract":"This paper investigates the introduction of biologically inspired intelligence into virtual assembly. It develops an approach to assist product engineers making assembly-related manufacturing decisions without actually realizing the physical products. This approach extracts the knowledge of mechanical assembly by allowing human operators to perform assembly operations directly in the virtual environment. The incorporation of a biologically inspired neural network into an interactive assembly planner further leads to the improvement of flexible product manufacturing, i.e., automatically producing alternative assembly sequences with robot-level instructions for evaluation and optimization. Complexity analysis and simulation study demonstrate the effectiveness and efficiency of this approach.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"69 1","pages":"159-167"},"PeriodicalIF":0.0,"publicationDate":"2003-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81442180","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 : 2002-12-10DOI: 10.1109/TSMCC.2002.801357
M. Oosterom, Robert Babuška, H. Verbruggen
A sensor management system based on soft computing techniques has been developed and implemented in the flight control system of a small commercial aircraft. Unlike in the conventional sensor management system, the signals from sensors are assigned weights based on fuzzy membership functions and the consolidated signal is computed as a weighted average. This approach improves the quality of the consolidated signal and reduces transients due to sensor failures. This soft voting is extended to soft flight control law reconfiguration. In addition, a virtual sensor has been introduced as an arbitrator which enables the isolation of the failed sensor in the duplex operation and the detection of a sensor failure in the simplex operation. The effectiveness of the proposed methods is demonstrated by using an extensive simulation model of a small commercial aircraft, developed by airframe and control system manufacturers on the basis of an existing business jet. Furthermore, the system has been successfully evaluated and compared to standard techniques by means of pilot-in-the-loop simulations on the Research Flight Simulator of the National Aerospace Laboratory in The Netherlands. This application, developed within a Brite/EuRam research project, is characterized by the effective combination of novel soft computing techniques with standard, well proven methods of the aircraft industry. The properties of the conventional sensor management system have been retained, with the additional advantage that the quality of the consolidated signal is improved, the failure-induced transients are reduced, and the consolidated signal remains available up to the last valid sensor.
{"title":"Soft computing applications in aircraft sensor management and flight control law reconfiguration","authors":"M. Oosterom, Robert Babuška, H. Verbruggen","doi":"10.1109/TSMCC.2002.801357","DOIUrl":"https://doi.org/10.1109/TSMCC.2002.801357","url":null,"abstract":"A sensor management system based on soft computing techniques has been developed and implemented in the flight control system of a small commercial aircraft. Unlike in the conventional sensor management system, the signals from sensors are assigned weights based on fuzzy membership functions and the consolidated signal is computed as a weighted average. This approach improves the quality of the consolidated signal and reduces transients due to sensor failures. This soft voting is extended to soft flight control law reconfiguration. In addition, a virtual sensor has been introduced as an arbitrator which enables the isolation of the failed sensor in the duplex operation and the detection of a sensor failure in the simplex operation. The effectiveness of the proposed methods is demonstrated by using an extensive simulation model of a small commercial aircraft, developed by airframe and control system manufacturers on the basis of an existing business jet. Furthermore, the system has been successfully evaluated and compared to standard techniques by means of pilot-in-the-loop simulations on the Research Flight Simulator of the National Aerospace Laboratory in The Netherlands. This application, developed within a Brite/EuRam research project, is characterized by the effective combination of novel soft computing techniques with standard, well proven methods of the aircraft industry. The properties of the conventional sensor management system have been retained, with the additional advantage that the quality of the consolidated signal is improved, the failure-induced transients are reduced, and the consolidated signal remains available up to the last valid sensor.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"64 1","pages":"125-139"},"PeriodicalIF":0.0,"publicationDate":"2002-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78937133","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 : 2002-11-01DOI: 10.1109/TSMCC.2002.806072
J. Corchado, Jim Aiken
An approach to hybrid artificial intelligence problem solving is presented in which the aim is to forecast, in real time, the physical parameter values of a complex and dynamic environment: the ocean. In situations in which the rules that determine a system are unknown or fuzzy, the prediction of the parameter values that determine the characteristic behavior of the system can be a problematic task. In such a situation, it has been found that a hybrid artificial intelligence model can provide a more effective means of performing such predictions than either connectionist or symbolic techniques used separately. The hybrid forecasting system that has been developed consists of a case-based reasoning system integrated with a radial basis function artificial neural network. The results obtained from experiments in which the system operated in real time in the oceanographic environment, are presented.
{"title":"Hybrid artificial intelligence methods in oceanographic forecast models","authors":"J. Corchado, Jim Aiken","doi":"10.1109/TSMCC.2002.806072","DOIUrl":"https://doi.org/10.1109/TSMCC.2002.806072","url":null,"abstract":"An approach to hybrid artificial intelligence problem solving is presented in which the aim is to forecast, in real time, the physical parameter values of a complex and dynamic environment: the ocean. In situations in which the rules that determine a system are unknown or fuzzy, the prediction of the parameter values that determine the characteristic behavior of the system can be a problematic task. In such a situation, it has been found that a hybrid artificial intelligence model can provide a more effective means of performing such predictions than either connectionist or symbolic techniques used separately. The hybrid forecasting system that has been developed consists of a case-based reasoning system integrated with a radial basis function artificial neural network. The results obtained from experiments in which the system operated in real time in the oceanographic environment, are presented.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"15 1","pages":"307-313"},"PeriodicalIF":0.0,"publicationDate":"2002-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77778304","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 : 2002-11-01DOI: 10.1109/TSMCC.2002.806071
B. Kumar, P. Venkataram
In mobile networks, the traffic fluctuation is unpredictable due to mobility and varying resource requirement of multimedia applications. Hence, it is essential to maintain traffic within the network capacity to provide service guarantees to running applications. This paper proposes an admission control (AC) scheme in a mobile cellular environment supporting hand-off and new application traffic. In the case of multimedia applications, each applications has its own distinct range of acceptable quality of service (QoS) requirements. The network provides the service by maintaining the application specified QoS range. We propose a linear programming resource reduction (LP-RR) principle for admission control by maintaining QoS guarantees to existing applications and to increase the percentage of admission to hand-off and new applications. Artificial neural networks are used to solve the linear programming problem, which facilitates in real time admission control decision in the practical systems. We present an analytical model and results for the proposed AC scheme with resource reduction principle and a simulation study of the AC for performance evaluation. The simulation results demonstrate that the proposed AC scheme performs well in terms of increasing the number of admitted applications and maintains higher percentage of resource utilization. The suggested principle also shown that it is appropriate for the fair resource allocation with improved resource utilization.
{"title":"A LP-RR principle-based admission control for a mobile network","authors":"B. Kumar, P. Venkataram","doi":"10.1109/TSMCC.2002.806071","DOIUrl":"https://doi.org/10.1109/TSMCC.2002.806071","url":null,"abstract":"In mobile networks, the traffic fluctuation is unpredictable due to mobility and varying resource requirement of multimedia applications. Hence, it is essential to maintain traffic within the network capacity to provide service guarantees to running applications. This paper proposes an admission control (AC) scheme in a mobile cellular environment supporting hand-off and new application traffic. In the case of multimedia applications, each applications has its own distinct range of acceptable quality of service (QoS) requirements. The network provides the service by maintaining the application specified QoS range. We propose a linear programming resource reduction (LP-RR) principle for admission control by maintaining QoS guarantees to existing applications and to increase the percentage of admission to hand-off and new applications. Artificial neural networks are used to solve the linear programming problem, which facilitates in real time admission control decision in the practical systems. We present an analytical model and results for the proposed AC scheme with resource reduction principle and a simulation study of the AC for performance evaluation. The simulation results demonstrate that the proposed AC scheme performs well in terms of increasing the number of admitted applications and maintains higher percentage of resource utilization. The suggested principle also shown that it is appropriate for the fair resource allocation with improved resource utilization.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"33 1","pages":"293-306"},"PeriodicalIF":0.0,"publicationDate":"2002-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78899779","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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