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11th International Conference on Control, Automation and Systems (ICCAS)/Robot World Conference

作者： Seo, JiHye Kong, NamWoong Park, PooGyeon POSTECH Div IT Convergence Engn WCU Pohang Kyeongbuk South Korea POSTECH Dept Elect Engn Pohang South Korea

ISBN: (纸本)9788993215038

This paper proposes a normalized LMS algorithm which automatically determines the number of orthogonal correction factors using an evolutionary method. The evolutionary method increases or decreases the number of orthogonal correction factors by comparing the squared output errors with some threshold. The experimental results show that the proposed algorithm has not only a fast convergence rate and a small steady-state estimation error but also lower computational complexity than the existing algorithms with multiple input vectors.

关键词： Adaptive filters NLMS-OCF evolutionary method

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Hierarchical Fuzzy System Modeling by Genetic and Bacterial Programming Approaches

Hierarchical Fuzzy System Modeling by Genetic and Bacterial ...

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2010 IEEE World Congress on Computational Intelligence

作者： Balazs, Krisztian Botzheim, Janos Koczy, Laszlo T. Budapest Univ Technol & Econ Dept Telecommun & Media Informat H-1117 Budapest Hungary Szechenyi Istvan Univ Dept Automat Gyor Hungary Szechenyi Istvan Univ Inst Informat Elect & Mech Engn Fac Engn Sci Gyor Hungary Budapest Univ Technol & Econ Dept Telecommun & Media Informat Budapest Hungary

ISBN: (纸本)9781424469208

In this paper a method is proposed for constructing hierarchical fuzzy rule bases in order to model black box systems defined by input-output pairs, i.e. to solve supervised machine learning problems. The resultant hierarchical rule base is the knowledge base, which is constructed by using structure constructing evolutionary techniques, namely, Genetic and Bacterial Programming Algorithms. Applying hierarchical fuzzy rule bases is a way of reducing the complexity of the knowledge base, whereas evolutionary methods ensure a relatively efficient learning process. This is the reason of the investigation of this combination.

关键词： bacterial programming algorithm black box system evolutionary method fuzzy systems genetic algorithms genetic programming algorithm hierarchical fuzzy rule bases hierarchical fuzzy system hierarchical systems knowledge base complexity reduction knowledge based systems learning (artificial intelligence) logic programming machine learning

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Improved Particle Swarm Optimization approach for Classification by using LDA 9

Improved Particle Swarm Optimization approach for Classifica...

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IEEE 9th International Conference on Intelligent Systems and Control (ISCO)

作者： Nema, S. Thakur, S. S. Mahatma Gandhi Chitrakoot Gramodaya Vishwavidyala Dept Comp Sci & Engn Satna Madhya Pradesh India Jabalpur Engn Coll Dept Appl Math Jabalpur Madhya Pradesh India

ISBN: (纸本)9781479964802

In this paper, Improved Particle Swarm Optimization (IPSO) approach is used in feature selection process - Linear Discriminant Analysis (LDA). This evolutionary random search method enhanced the classification rate with less computational time. The effectiveness of the proposed IPSO-LDA method is verified by employed Indian Face Database (IFD) and compare the results with existing methods.

关键词： Particle Swarm Optimization (PSO) Linear Discriminant Analysis (LDA) Classification Feature Extraction evolutionary method

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Concept analysis of coping with multiple sclerosis

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International Journal of Nursing Sciences 2018年第2期5卷 168-173页

作者： Ali Dehghani Abdolkhalegh Keshavarzi Mohsen Faseleh Jahromi Sara Shahsavari isfahani Soheila Keshavarzi School of Nursing and Paramedical Jahrom University of Medical ScienceJahromIran Research Center for Noncommunicable Diseases Jahrom University of Medical SciencesJahromIran Department of General Surgery School of MedicineMember of Shiraz Burn Research CenterShiraz University of Medical SciencesShirazIran Department of Counseling Faculty of Psychology and Educational SciencesIslamic Azad UniversityMarvdasht BranchMarvdashtIran

Objective:The concept of coping with disease appears frequently in the literature;however,there is no precise definition of *** aim of this study is to clarify coping concept,and to identify its attributes,antecedents,and consequences in patients with multiple ***:Rodgers'evolutionary method of concept analysis was used to clarify the concept of coping.A literature review was conducted with key terms‘multiple sclerosis’,‘coping’,‘adjustment’,and‘deal with’.After searching databases,1370 papers were found for the period ***,55 articles and texts were selected for *** analysis was carried out using thematic *** independent researcher checked the process to ensure credibility and reduce personal ***:Coping with multiple sclerosis is a multidimensional concept with three main attributes:maintenance of emotional balance,acceptance of the disease,and *** support,awareness toward the disease,attitude toward the disease,and religious-spiritual beliefs were found as *** promotion,adherence to treatment regimen,independence in personal life and social relationships,and improvement of family relationships were found as consequences of these ***:These findings not only add to the body of knowledge in health science,but also serve as an important motivation for further theory development and research in this *** and health professions can also benefit from a deeper understanding of coping concept in providing and planning healthcare for these patients.

关键词： Concept analysis Coping evolutionary method Multiple sclerosis

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Fuzzy Control of Parameters to Dynamically Adapt the PSO and GA Algorithms

Fuzzy Control of Parameters to Dynamically Adapt the PSO and...

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2010 IEEE World Congress on Computational Intelligence

作者： Valdez, Fevrier Melin, Patricia Castillo, Oscar Tijuana Inst Technol Div Grad Studies & Res Tijuana Mexico

ISBN: (纸本)9781424469208

We describe in this paper a new hybrid approach for mathematical function optimization combining Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) using Fuzzy Logic for parameter adaptation and integrate the results. The new evolutionary method combines the advantages of the fuzzy logic to give us an improved FPSO+FGA hybrid method. Fuzzy Logic is used to combine the results of the PSO and GA in the best way possible. The new hybrid FPSO+FGA approach is compared with the PSO and GA methods with a set of benchmark mathematical functions. The new hybrid FPSO+FGA method is shown to be superior to the individual evolutionary methods on the set of benchmark functions.

关键词： evolutionary method fuzzy control fuzzy control fuzzy logic fuzzy logic genetic algorithms genetic algorithms parameter adaptation particle swarm optimisation particle swarm optimization

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Finance Time Series Prediction Using Complex-valued Flexible Neural Tree Model 13

Finance Time Series Prediction Using Complex-valued Flexible...

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13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

作者： Yang, Bin Zhang, Wei Gong, Li-Na Ma, Huai-Zhi Zaozhuang Univ Sch Informat Sci & Engn Zaozhuang Peoples R China

ISBN: (纸本)9781538621653

In this paper, we present a novel time series prediction model based on complex-valued flexible neural tree (CVFNT) model to improve the forecasting accuracy. In a CVFNT model, data, parameters and activation functions are complex-valued. The evolutionary method based on the modified genetic algorithm (GP) and artificial bee colony (ABC) is used to evolve the CVFNT model. Two real time series datasets from Shanghai stock index and exchange rates between Euro and US Dollar are used to test CVFNT model. Results reveal that our proposed method can predict more accurately finance time series than real-valued classic neural networks (RVNN) and complex-valued neural network (CVNN).

关键词： evolutionary method flexible neural tree complex-valued artificial bee colony

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Index Fund Rebalancing Using Probabilistic Model-building Genetic Algorithm with Narrower Width Histograms

Index Fund Rebalancing Using Probabilistic Model-building Ge...

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2010 IEEE World Congress on Computational Intelligence

作者： Orito, Yukiko Sugizaki, Shota Yamamoto, Hisashi Tsujimura, Yasuhiro Kambayashi, Yasushi Hiroshima Univ Grad Sch Social Sci 1-2-1 Kagamiyama Hiroshima 7398525 Japan Nippon Inst Technol Dept Comp & Engn JP-3458501 Urawa Saitama Japan

ISBN: (纸本)9781424481262

The portfolio optimization/rebalancing problem is to determine a proportion-weighted combination in a portfolio in order to achieve certain investment targets. For this problem, many researchers have used various evolutionary methods and models such as genetic algorithms and simulated annealing. On the other hand, the portfolio optimization/rebalancing problem can be viewed as a multi-dimensional problem because its solution is a proportion-weighted combination for the given assets. The previous works, however, have not taken into account the multi-dimensional aspect of the problem. In order to approach this problem from the multi-dimensional aspect, we propose a model based on the probabilistic model-building genetic algorithm with narrower width histograms (PMBGA-NWH), and then apply it to optimize the constrained index funds with the given rebalancing cost in this paper. In the numerical experiments, we show that our model has better ability to make optimal index funds than the traditional genetic algorithm (GA).

关键词： evolutionary method genetic algorithms index fund rebalancing investment investment targets multidimensional problem portfolio optimization probabilistic model-building genetic algorithm probability rebalancing problem simulated annealing width histograms

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MULTI-AGENT AND MARKET BASED DYNAMIC OPTIMIZATION AND ITS EXTENSIONS TODISTRIBUTED SUPPLY CHAIN PROCUREMENT PLANNING PROBLEMS

MULTI-AGENT AND MARKET BASED DYNAMIC OPTIMIZATION AND ITS EX...

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作者： Tang, Kaizhi PennState University Libraries

学位级别：Doctor of Philosophy

This thesis discusses distributed computational methodologies used for solving supply chain procurement planning problems with information systems naturally distributed at different locations. The planning problem is heavily influenced by transportation costs, whose calculation is based on a stochastic environmentwith random service and travel times. The main contributions of this thesis are the computational methodologies that solve the problem under different conditions. All these methodologies are developed in the context of supply chain procurement planning, but they are not necessarily restricted to this context. They can be modified and adapted to other distributed planning and scheduling *** Double Auction Market Mechanism (DAMM) is an innovative distributed negotiation mechanism for supply chain procurement planning. It is developed to achieve a common objective among multiple individual decision makers by modeling their respective interests in a virtual market for trading transportation tasks. The trading mechanism emulates the double auction institutions of a real market. For trading, double auction institutions enable exchange of transportation tasks among a transportation company and its trucks, which are modeled as software agents. An agent's decision making among market interactions is based on a set of stochastic rules, which consider its self-interest with the support of transportation cost evaluation. Iterated task exchange among agents drives the task allocation to Pareto optimality, which is derived from the concept of market equilibrium. DAMM is an any-time negotiationprotocol, so it is useful for dynamic ptimization and contingency planning.A Coordinated Reinforcement Learning (CRL) method is developed to refine the distributed transportation plans generated by distributed heuristics based on DAMM. Through analyzing the drawbacks of the distributed double auctionheuristic due to its strict market rules, we enable the task agents in the

关键词： double auction market mechanism supply chain procurement transportation planning multi-agent system contingency planning reinforcement learning meta-heuristic variable neighborhood search dynamic optimization distributed heuristic multi-stage game evolutionary method fictitious playing evolutionary stable strategy

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Inference of Differential Equation Models by Multi Expression Programming for Gene Regulatory Networks

Inference of Differential Equation Models by Multi Expressio...

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5th International Conference on Intelligent Computing

作者： Yang, Bin Chen, Yuehui Meng, Qingfang Univ Jinan Computat Intelligence Lab Sch Informat Sci & Engn Jinan 250022 Peoples R China

ISBN: (纸本)9783642040191

This paper presents an evolutionary method for identifying the gene regulatory network from the observed time series data of gene expression using a system of ordinary differential equations (ODEs) as a model of network. The structure of ODE is inferred by the Multi Expression Programming (MEP) and the ODE's parameters are optimized by using particle swarm optimization (PSO). The proposed method can acquire the best structure of the ODE only by a small population, and also by partitioning the search space of system of ODEs can be reduced significantly. The effectiveness and accuracy of the proposed method are demonstrated by using synthesis data from the artificial genetic networks.

关键词： evolutionary method multi expression programming ordinary differential equations particle swarm optimization artificial genetic networks

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Investigating european culture from a psychological viewpoint

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World Futures 1989年第1期26卷 53-56页

作者： Munari, Alberto University of Geneva International Center for Cultural Psychology Geneva Switzerland

Myths, stereotypes, projections and imperialisms that often encumber cultural investigations are pinpointed. More particularly, the questionnaire method is criticized as being unable to verify the real meaning that a concept may have for the individual subject.A new methodological approach, called “evolutionary method,” is suggested in order to grasp not only the concepts an individual or a group may be able to elaborate, but also the emotional relationship he entertains with them. The evolutionary method, by its special use of metaphors, analogies and other images, allows the researcher to bypass linguistic barriers and biases, and thus to unveil, without reducing it, the complexity of interrelations between systems of values and systems of conceptualizations.

关键词： culture evolutionary method interviewing

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