{"title":"A case-based recommender for task assignment in heterogeneous computing systems","authors":"S. Ghanbari, M. Meybodi, K. Badie","doi":"10.1109/ICHIS.2004.1","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.1","url":null,"abstract":"Case-based reasoning (CBR) is a knowledge-based problem-solving technique, which is based on reuse of previous experiences. We propose a new model for static task assignment in heterogeneous computing systems. The proposed model is a combination of the case based reasoning and the learning automata model. In this new model a learning automata model is used as adaptation mechanism, which adapts previously experienced cases to the problem to be solved. The objective of the proposed model is to reduce the number of iterations required to find a semioptimum solution. The application is modeled as a set of independent tasks and the heterogeneous computing system is modeled as a network of machines. Using computer simulation, it is shown that the combined model outperforms the model that only uses learning automata.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121237408","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}
{"title":"Neural networks and belief logic","authors":"Y. Chen, Joseph J. Chen","doi":"10.1109/ICHIS.2004.72","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.72","url":null,"abstract":"Many researchers have observed that neurons process information in an imprecise manner - if a logical inference emerges from neural computation, it is inexact at best. Thus, there must be a profound relationship between belief logic and neural networks. In Chen (2002), a plausible neural network model that can compute probabilistic and possibilistic logic was proposed. In this article we further extend this model to continuous variables for function and relation estimation. We discuss why and how belief logic is derived from neural computation.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116167404","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}
{"title":"Q'tron neural networks for constraint satisfaction","authors":"T. Yue, Mei-Ching Chen","doi":"10.1109/ICHIS.2004.77","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.77","url":null,"abstract":"This paper proposes the methods to solve the constraint satisfaction problems (CSPs) using Q'tron neural networks (NNs). A Q'tron NN is local-minima free if it is built as a known-energy system and is incorporated with the proposed persistent noise-injection mechanism. The so-built Q 'tron NN, as a result, settle down if and only if a feasible solution is found. Additionally, such a Q'tron NN is intrinsically auto-reversible. This renders the NN operable in a question-answering mode for extracting interested information. A concrete example, i.e., to solve the N-queen problem, is demonstrated to highlight the main concept.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"80 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131282758","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}
Laetitia Vermeulen-Jourdan, D. Corne, D. Savić, G. Walters
{"title":"Hybridising rule induction and multi-objective evolutionary search for optimising water distribution systems","authors":"Laetitia Vermeulen-Jourdan, D. Corne, D. Savić, G. Walters","doi":"10.1109/ICHIS.2004.58","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.58","url":null,"abstract":"In this article, we present our latest work with a hybrid multiobjective evolutionary algorithm called LEMMO (learnable evolution model for multiobjective optimization) which integrates machine learning into evolutionary search based on Michalski's \"LEM\" approach. The objective is to both improve the performance of the MOEA and to reduce the number of evaluations needed when used for optimising the design of water distribution networks (where evaluations are highly computationally costly). We compare LEMMO with NSGA-II and conclude that our approach is very promising for improved speed and quality in the water systems optimisation domain.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132362601","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}
{"title":"A two-phase genetic and set partitioning approach for the vehicle routing problem with time windows","authors":"G. B. Alvarenga, G. Mateus","doi":"10.1109/ICHIS.2004.13","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.13","url":null,"abstract":"The vehicle routing problem with time windows (VRPTW) is a well-known and complex combinatorial problem, which has received considerable attention in recent years. Results from exact methods have been improved exploring parallel implementations and modern branch-and-cut techniques. However, 23 out of the 56 high order instances from Solomon's test set still remain unsolved. Additionally, in many cases a prohibitive time is needed to find the exact solution. Many efficient heuristic methods have been developed to make possible a good solution in a reasonable amount of time. Using travel distance as the main objective, this paper proposes a robust heuristic approach for the VRPTW using an efficient genetic algorithm and a set partitioning formulation. The tests were produced using both real numbers and truncated data type, making it possible to compare the results with previous heuristic and exact methods published. Furthermore, computational results show that the proposed heuristic approach outperforms all previous known heuristic methods in the literature, in terms of the minimal travel distance.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"61 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115572073","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}
{"title":"Reconfigurable amplifier circuits for adaptive sensor systems employing bio-inspiration","authors":"S. Lakshmanan, A. König","doi":"10.1109/ICHIS.2004.79","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.79","url":null,"abstract":"In particular primary electronics of sensor systems is strongly subject to deviations and degradations caused by environmental and manufacturing conditions. Current approaches cope with these challenges by calibration or trimming techniques. More recent approaches from the field of evolutionary electronics offer considerable extensions, incorporating also issues of fault-tolerance and self-repair. State-of-the-art evolvable analog hardware bases on field-programmable-transistor-arrays (FPTA) and start from primal soup for each new problem. Our work deals with the crucial issue to efficiently include the wealth of existing engineering design knowledge into the otherwise attractive concept. For the practically relevant task of sensor amplifiers, a particular flexible FPTA architecture is developed, verified and physically implemented in a 0.35 /spl mu/m CMOS technology.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122945627","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}
{"title":"A motivation based behavior in hybrid intelligent agents for intention reconsideration process in vessel berthing applications","authors":"Prasanna Lokuge, D. Alahakoon","doi":"10.1109/ICHIS.2004.6","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.6","url":null,"abstract":"Strategic planning and dynamism in decision making are essential factors in a vessel berthing application in any container port to assure faster turnaround time and high productivity. BDI agents have been used in many applications with limited capabilities. We propose a new hybrid BDI architecture with learning capacities overcoming some limitations exists in the generic BDI agent model. A new \"knowledge acquisition model\" (KAM) module is proposed with a supervised neural network and adaptive neuro fuzzy inference system (ANFIS) in the intention reconsideration process of the agent model. Commitment strategy of the new intention reconsideration process is based on the motivation of the state transitions and the effect of belief changes in the environment.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125421225","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}
{"title":"Field-programmable analog filters array with applications for fuzzy inference systems","authors":"S. Ionita, E. Sofron","doi":"10.1109/ICHIS.2004.45","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.45","url":null,"abstract":"Encouraged by the recent progress in the FPAA technology, we propose a flexible membership functions synthesis method based on the configurable filter blocks. Based on the actual paradigm of FPAA we consider an interesting and promising idea to implement the membership functions using the frequency-response curves of the analog filters. The other specific functional blocks can be implemented with programmable analog structures obtaining a complete unit for fuzzy inference processing.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114281455","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}
{"title":"Improvement of non-linear mapping computation for dimensionality reduction in data visualization and classification","authors":"K. Iswandy, A. König","doi":"10.1109/ICHIS.2004.60","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.60","url":null,"abstract":"The projection of high-dimensional data by linear or nonlinear techniques is a well established technique in pattern recognition and other scientific and industrial application fields. Commonly, methods affiliated to multidimensional-scaling, projection pursuit or Sammons nonlinear distance preserving mapping are applied, based on gradient descent techniques. These suffer from well-known dependence on initial or starting value and their limited ability to reach only local minimum. In this paper, stochastic search techniques are applied to the NLM to achieve lower residual stress or error value in competitive time. Encouraging results have been obtained for a particular developed local algorithm both with regard to convergence time and residual error.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125897470","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}
{"title":"A constructive approach to creating a method for generating images","authors":"K. Ohnishi, Kaori Yoshida","doi":"10.1109/ICHIS.2004.2","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.2","url":null,"abstract":"This paper proposes a constructive approach to creating a method for generating images, which acquires mechanisms to draw images that users provide. The constructive approach relies on a combination of production rules and an optimization technique. The method realized based on the concept of the constructive approach combines simple production rules for cellular automata with a genetic algorithm. The realized method is applied to creating methods for generating simple binary images, and the results show that the proposed approach is capable of acquiring mechanisms to draw given images.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129899692","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}