To confront the Resource Constrained Project Scheduling Problem (RCPSP), metaheuristics have been... more To confront the Resource Constrained Project Scheduling Problem (RCPSP), metaheuristics have been proved very good alternatives, especially for large complicated projects. In this class of algorithms, Evolutionary Computation has recently gained much attention, with most important representative the Genetic Algorithms. Following the mainstream, we stress our efforts on another evolutionary algorithm, the Evolution Strategies (ES). The application of ES takes place under two discrete solution encodings; one works on vectors of priority values and the other is based on convex combinations of priority rules. The analysis of the results, produced from tests on the PSPLIB, inspired the development of two extended algorithms. The first extension assumes that ES work on vectors of priority values but the underlying evolutionary operators are modified so as to allow a fast reordering of activities. The second extension concerns the construction of a novel solution encoding which combines the priority values and the convex combination of priority rules. Both proposals indicate a far better performance when compared with genetic algorithms, hence, open a new research direction in the domain of project scheduling with evolutionary algorithms.
Auctioning over Wireless Networks, constitutes an attractive emerging class for m-commerce applic... more Auctioning over Wireless Networks, constitutes an attractive emerging class for m-commerce applications and formulates a procurement negotiation tool supporting the announcement and execution of geographically focused auctions. This is feasible by using the Location-Based Services (LBS), which resulted from the unification of automatic position sensing (GPS) and wireless connectivity. The present article aims to analyse and match the properties of heterogeneous wireless networks (mobile, GPS) and to set a framework for the development of Reverse M-Auction based Marketplaces operating in a location sensitive context with application in freight services procurement. A location-sensitive, reverse, M-auction application in the freight transport market where potential suppliers (carriers) are able to place bids for Less-Than-Truckload (LTL) shipments or during empty trips while on the move aiming to gain from economies of scope, is the application examined in this chapter.
Vessels typically house large sets of different, complex types of equipment; functional failures ... more Vessels typically house large sets of different, complex types of equipment; functional failures in them lead to operational stoppage or downgrade with impacts on performance, quality and/or cost. Preventive maintenance schedules are commonly employed, the optimization of which relates to the need of maintenance, the specific component where a problem is detected, the identified fault type, the severity, the expected remaining life within acceptable performance (confidence) limits, etc. Recent advances in sensors and in Machine Learning (ML) methods, have boosted both the fault diagnosis and prognosis, thus incenting companies to invest on the development of efficient Predictive Maintenance (PdM). In this work, we explore the PdM problem for a family of equipment, namely, compressors, through the application of ML techniques on large datasets obtained from on-board sensors. We first deal with the problem of identifying the most useful features in the frequency and time domains, that...
IEEE 2001 International Conference on Image Processing (ICIP 2001) (Cat. No.01CH37205), 2001
ABSTRACT Optical character recognition (OCR) encompasses a large number of applications, which ha... more ABSTRACT Optical character recognition (OCR) encompasses a large number of applications, which have appeared in the scientific literature. The spectrum of applications ranges from simple character recognition of printed sets to advanced handwritten text recognition, and has yielded satisfactory results in many cases. The present work focuses on the recognition of the alphanumeric content in car license plates within a semi-structured environment, using the adept vision system. A systematic approach, addressing extensively the associated theoretical and practical issues, was developed and is presented. The approach utilizes the adept assembly and information management environment to integrate in a single system the acquisition and digital image processing stages with the system training and the results interpretation. Several tests were conducted in order to evaluate the performance of the system and to analyze its sensitivity. The obtained results demonstrate the robustness of the system and the feasibility of operation in outdoor environments
10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297)
ABSTRACT The expansion of advanced modeling tools, such as neural, evolutionary, fuzzy and hybrid... more ABSTRACT The expansion of advanced modeling tools, such as neural, evolutionary, fuzzy and hybrid systems, has led to a systematic attempt for their applicability in the challenging stock market field. Today, the ensuing results are admittedly far better than those accomplished by models based on linear or typical nonlinear mathematical approximators; yet, the related trading risk remains at significantly high levels. In quest of innovative approaches, one interesting research direction appears to be the complete analysis and exploitation of various interrelated quantitative and mostly qualitative agents affecting stock market behavior. Based on this criterion, fuzzy cognitive maps (FCMs) constitute a powerful modeling tool for the development of a stock market forecasting system as they are structured as networks of cause-effect relationships between diverse factors. The subject of this study is aligned with the aforementioned remark; firstly, the recognition of crucial stock market, business and economic agents is attempted, secondly an FCM-based stock market model is designed, and ultimately the feasibility and effectiveness of the real world application is evaluated
10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297)
ABSTRACT Fuzzy cognitive maps constitute one of the most dynamically evolving areas of qualitativ... more ABSTRACT Fuzzy cognitive maps constitute one of the most dynamically evolving areas of qualitative network representation. The origin of this progress ties mainly in their endogenous advantageous modeling features, which are simplicity, adaptability, capability of approximating abstractive structures, and white box operation. These characteristics prove their significance when managing cognitive processes. Attempting to broaden FCM functionality and applicability, developers should stress on real world problems and situations, sustaining in parallel the aforementioned modeling capabilities. Following this direction, two distinctive elements of typical cognition and decision making systems can be taken into account: the conditional effects and the notion of synergy. This paper captures the importance of these concepts when pursuing the accuracy and effectiveness in causal network representations and introduces mathematical formalisms for incorporating them in the FCM inference engine. Most of all, the benefits of the proposed schemes are in accordance to the practical framework of FCMs - ease of use combined with operational flexibility and wide adaptability
IEEE International Engineering Management Conference
ABSTRACT The evaluation of R&D projects in a high technology firm is very important. ... more ABSTRACT The evaluation of R&D projects in a high technology firm is very important. A lot of them quite often do not lead to new products as management did not take into consideration indexes such as probability of commercial success, technological success, strategic fit, etc which cannot be expressed in a quantitative form. An efficient and reliable approach for evaluating R&D projects capable of handling simultaneously the quantitative and qualitative criteria involved based on the theory of fuzzy logic is presented and a software model of the approach has been developed and tested in a real environment. It is a multiple criteria decision-making method where all projects are rated according to a number of quantitative and qualitative criteria capturing possibilities of technical and commercial success and the consistency of the projects with business strategy. We report on the criteria used for the evaluation of the projects and on the operation of the software model.
Foundations of Computing and Decision Sciences, 2005
Streszczenie angielskie: The cost of support for an expensive military system during its "in... more Streszczenie angielskie: The cost of support for an expensive military system during its "in-service" phase of its life often exceeds the two-thirds of the entire life cycle cost. The support of a system in a military operational environment is the main subject of the Logistics ...
Fuzzy Sets in Management, Economics and Marketing, 2001
AbstractStock price forecasting constitutes a challenging research area. Diverse schemes (such as... more AbstractStock price forecasting constitutes a challenging research area. Diverse schemes (such as regression models, neural networks, neurofuzzy systems etc.) have been developed and applied; yet, the overall prediction behavior of such systems is questionable in real world conditions. The major reason limiting the accurate stock price predictions is the existence of a plethora of interrelated agents (quantitative and qualitative) affecting stock price movements and fluctuations. Fuzzy Cognitive Maps (FCMs) seem to constitute a useful modeling tool for the development of a forecasting model, which takes into account the characteristics of the stock market. The main purpose of this work is thus to present analytically the FCM operation mode and the potential extensions of the underlying inference mechanism, and to describe possible applications of FCMs in the domain of stock market.
10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297)
ABSTRACT FCMs were presented in the middle eighties and extended through studies, which enhanced ... more ABSTRACT FCMs were presented in the middle eighties and extended through studies, which enhanced the basic principles and proposed domains of successful application. The special scientific interest about FCMs is due to their favorable characteristics, in conjunction with the representation ability and the inference mechanism. Indeed, FCMs embrace flexibility, functionality and simplicity, while simultaneously they maintain the advantageous features of typical fuzzy systems. Although the core concepts of FCM theory have been clarified, robustness of the functional framework is still under question, as various aspects have not been explicitly described and in many cases, the current practice seems to restrict efficiency and credibility. The present work aims to improve the FCM background by conducting a thorough analysis of the basic principles, exposing modifications of the operating framework and, mainly, introducing an innovative inference procedure that manages more reasonably multi-stimulus situations, which constitute a common phenomenon in the real world
International Journal of Computational Cognition (http://www.YangSky.com/yangijcc.htm) Volume 1, ... more International Journal of Computational Cognition (http://www.YangSky.com/yangijcc.htm) Volume 1, Number 2, Pages 4165, June 2003 Publisher Item Identifier S 1542-5908(03)10203-5/$20.00 Article electronically published on November 15, 2002 at http://www.YangSky.com/ijcc12. ...
... Development of dynamic cognitive networks as complex systems approximators: validation in fin... more ... Development of dynamic cognitive networks as complex systems approximators: validation in financial time series. ... DCNs have the capabilities to model and manage nonlinear andtime-dependent behaviors ... that was eventually adopted to build up a stock price forecasting system ...
To confront the Resource Constrained Project Scheduling Problem (RCPSP), metaheuristics have been... more To confront the Resource Constrained Project Scheduling Problem (RCPSP), metaheuristics have been proved very good alternatives, especially for large complicated projects. In this class of algorithms, Evolutionary Computation has recently gained much attention, with most important representative the Genetic Algorithms. Following the mainstream, we stress our efforts on another evolutionary algorithm, the Evolution Strategies (ES). The application of ES takes place under two discrete solution encodings; one works on vectors of priority values and the other is based on convex combinations of priority rules. The analysis of the results, produced from tests on the PSPLIB, inspired the development of two extended algorithms. The first extension assumes that ES work on vectors of priority values but the underlying evolutionary operators are modified so as to allow a fast reordering of activities. The second extension concerns the construction of a novel solution encoding which combines the priority values and the convex combination of priority rules. Both proposals indicate a far better performance when compared with genetic algorithms, hence, open a new research direction in the domain of project scheduling with evolutionary algorithms.
Auctioning over Wireless Networks, constitutes an attractive emerging class for m-commerce applic... more Auctioning over Wireless Networks, constitutes an attractive emerging class for m-commerce applications and formulates a procurement negotiation tool supporting the announcement and execution of geographically focused auctions. This is feasible by using the Location-Based Services (LBS), which resulted from the unification of automatic position sensing (GPS) and wireless connectivity. The present article aims to analyse and match the properties of heterogeneous wireless networks (mobile, GPS) and to set a framework for the development of Reverse M-Auction based Marketplaces operating in a location sensitive context with application in freight services procurement. A location-sensitive, reverse, M-auction application in the freight transport market where potential suppliers (carriers) are able to place bids for Less-Than-Truckload (LTL) shipments or during empty trips while on the move aiming to gain from economies of scope, is the application examined in this chapter.
Vessels typically house large sets of different, complex types of equipment; functional failures ... more Vessels typically house large sets of different, complex types of equipment; functional failures in them lead to operational stoppage or downgrade with impacts on performance, quality and/or cost. Preventive maintenance schedules are commonly employed, the optimization of which relates to the need of maintenance, the specific component where a problem is detected, the identified fault type, the severity, the expected remaining life within acceptable performance (confidence) limits, etc. Recent advances in sensors and in Machine Learning (ML) methods, have boosted both the fault diagnosis and prognosis, thus incenting companies to invest on the development of efficient Predictive Maintenance (PdM). In this work, we explore the PdM problem for a family of equipment, namely, compressors, through the application of ML techniques on large datasets obtained from on-board sensors. We first deal with the problem of identifying the most useful features in the frequency and time domains, that...
IEEE 2001 International Conference on Image Processing (ICIP 2001) (Cat. No.01CH37205), 2001
ABSTRACT Optical character recognition (OCR) encompasses a large number of applications, which ha... more ABSTRACT Optical character recognition (OCR) encompasses a large number of applications, which have appeared in the scientific literature. The spectrum of applications ranges from simple character recognition of printed sets to advanced handwritten text recognition, and has yielded satisfactory results in many cases. The present work focuses on the recognition of the alphanumeric content in car license plates within a semi-structured environment, using the adept vision system. A systematic approach, addressing extensively the associated theoretical and practical issues, was developed and is presented. The approach utilizes the adept assembly and information management environment to integrate in a single system the acquisition and digital image processing stages with the system training and the results interpretation. Several tests were conducted in order to evaluate the performance of the system and to analyze its sensitivity. The obtained results demonstrate the robustness of the system and the feasibility of operation in outdoor environments
10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297)
ABSTRACT The expansion of advanced modeling tools, such as neural, evolutionary, fuzzy and hybrid... more ABSTRACT The expansion of advanced modeling tools, such as neural, evolutionary, fuzzy and hybrid systems, has led to a systematic attempt for their applicability in the challenging stock market field. Today, the ensuing results are admittedly far better than those accomplished by models based on linear or typical nonlinear mathematical approximators; yet, the related trading risk remains at significantly high levels. In quest of innovative approaches, one interesting research direction appears to be the complete analysis and exploitation of various interrelated quantitative and mostly qualitative agents affecting stock market behavior. Based on this criterion, fuzzy cognitive maps (FCMs) constitute a powerful modeling tool for the development of a stock market forecasting system as they are structured as networks of cause-effect relationships between diverse factors. The subject of this study is aligned with the aforementioned remark; firstly, the recognition of crucial stock market, business and economic agents is attempted, secondly an FCM-based stock market model is designed, and ultimately the feasibility and effectiveness of the real world application is evaluated
10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297)
ABSTRACT Fuzzy cognitive maps constitute one of the most dynamically evolving areas of qualitativ... more ABSTRACT Fuzzy cognitive maps constitute one of the most dynamically evolving areas of qualitative network representation. The origin of this progress ties mainly in their endogenous advantageous modeling features, which are simplicity, adaptability, capability of approximating abstractive structures, and white box operation. These characteristics prove their significance when managing cognitive processes. Attempting to broaden FCM functionality and applicability, developers should stress on real world problems and situations, sustaining in parallel the aforementioned modeling capabilities. Following this direction, two distinctive elements of typical cognition and decision making systems can be taken into account: the conditional effects and the notion of synergy. This paper captures the importance of these concepts when pursuing the accuracy and effectiveness in causal network representations and introduces mathematical formalisms for incorporating them in the FCM inference engine. Most of all, the benefits of the proposed schemes are in accordance to the practical framework of FCMs - ease of use combined with operational flexibility and wide adaptability
IEEE International Engineering Management Conference
ABSTRACT The evaluation of R&D projects in a high technology firm is very important. ... more ABSTRACT The evaluation of R&D projects in a high technology firm is very important. A lot of them quite often do not lead to new products as management did not take into consideration indexes such as probability of commercial success, technological success, strategic fit, etc which cannot be expressed in a quantitative form. An efficient and reliable approach for evaluating R&D projects capable of handling simultaneously the quantitative and qualitative criteria involved based on the theory of fuzzy logic is presented and a software model of the approach has been developed and tested in a real environment. It is a multiple criteria decision-making method where all projects are rated according to a number of quantitative and qualitative criteria capturing possibilities of technical and commercial success and the consistency of the projects with business strategy. We report on the criteria used for the evaluation of the projects and on the operation of the software model.
Foundations of Computing and Decision Sciences, 2005
Streszczenie angielskie: The cost of support for an expensive military system during its "in... more Streszczenie angielskie: The cost of support for an expensive military system during its "in-service" phase of its life often exceeds the two-thirds of the entire life cycle cost. The support of a system in a military operational environment is the main subject of the Logistics ...
Fuzzy Sets in Management, Economics and Marketing, 2001
AbstractStock price forecasting constitutes a challenging research area. Diverse schemes (such as... more AbstractStock price forecasting constitutes a challenging research area. Diverse schemes (such as regression models, neural networks, neurofuzzy systems etc.) have been developed and applied; yet, the overall prediction behavior of such systems is questionable in real world conditions. The major reason limiting the accurate stock price predictions is the existence of a plethora of interrelated agents (quantitative and qualitative) affecting stock price movements and fluctuations. Fuzzy Cognitive Maps (FCMs) seem to constitute a useful modeling tool for the development of a forecasting model, which takes into account the characteristics of the stock market. The main purpose of this work is thus to present analytically the FCM operation mode and the potential extensions of the underlying inference mechanism, and to describe possible applications of FCMs in the domain of stock market.
10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297)
ABSTRACT FCMs were presented in the middle eighties and extended through studies, which enhanced ... more ABSTRACT FCMs were presented in the middle eighties and extended through studies, which enhanced the basic principles and proposed domains of successful application. The special scientific interest about FCMs is due to their favorable characteristics, in conjunction with the representation ability and the inference mechanism. Indeed, FCMs embrace flexibility, functionality and simplicity, while simultaneously they maintain the advantageous features of typical fuzzy systems. Although the core concepts of FCM theory have been clarified, robustness of the functional framework is still under question, as various aspects have not been explicitly described and in many cases, the current practice seems to restrict efficiency and credibility. The present work aims to improve the FCM background by conducting a thorough analysis of the basic principles, exposing modifications of the operating framework and, mainly, introducing an innovative inference procedure that manages more reasonably multi-stimulus situations, which constitute a common phenomenon in the real world
International Journal of Computational Cognition (http://www.YangSky.com/yangijcc.htm) Volume 1, ... more International Journal of Computational Cognition (http://www.YangSky.com/yangijcc.htm) Volume 1, Number 2, Pages 4165, June 2003 Publisher Item Identifier S 1542-5908(03)10203-5/$20.00 Article electronically published on November 15, 2002 at http://www.YangSky.com/ijcc12. ...
... Development of dynamic cognitive networks as complex systems approximators: validation in fin... more ... Development of dynamic cognitive networks as complex systems approximators: validation in financial time series. ... DCNs have the capabilities to model and manage nonlinear andtime-dependent behaviors ... that was eventually adopted to build up a stock price forecasting system ...
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Papers by Dimitrios Emiris