Titlebook: Computational Intelligence and Decision Making; Trends and Applicati Ana Madureira,Cecilia Reis,Viriato Marques Conference proceedings 2013

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書目名稱Computational Intelligence and Decision Making影響因子(影響力)




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書目名稱Computational Intelligence and Decision Making網(wǎng)絡(luò)公開度




書目名稱Computational Intelligence and Decision Making網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Intelligence and Decision Making被引頻次




書目名稱Computational Intelligence and Decision Making被引頻次學(xué)科排名




書目名稱Computational Intelligence and Decision Making年度引用




書目名稱Computational Intelligence and Decision Making年度引用學(xué)科排名




書目名稱Computational Intelligence and Decision Making讀者反饋




書目名稱Computational Intelligence and Decision Making讀者反饋學(xué)科排名

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Comparison of Classification Methods for Golf Putting Performance Analysis,work, a digital camera was used to capture 30 trials of 6 expert golf players. The detection of the horizontal position of the golf club was performed using a computer vision technique followed by the estimation algorithm Darwinian Particle Swarm Optimization (DPSO) in order to obtain a kinematical

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Switched Unfalsified Multicontroller Nonparametric Model Based Design,nts. The overall control system can be viewed as a feedback interconnection of a SISO plant, a set of candidate controllers and a switched selection scheme that supervises the switching process among the candidate controllers. The switching scheme is designed without explicit assumptions on the plan

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Evaluating the Potential of Particle Swarm Optimization for Hyperspectral Image Clustering in Miniments are based on simple rules, but make complex overall behavior and search of the space. The clustering is the process of dividing the existing data to diverse groups based on the inherent characteristics and similarity of them and can also be seen as an optimization problem. Due to the complexity

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Efficient Discriminative Models for Proteomics with Simple and Optimized Features,ern subjects such as protein classification, where huge and complex datasets are common, and demand the most accurate and fast classifiers to retrieve meaningful biological traits in acceptable time. Although the Support Vector Machine algorithm has been playing a significant role by offering the mo

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Meta-heuristics Self-Parameterization in a Multi-agent Scheduling System Using Case-Based Reasoninge set up as efficient as possible in order to unsure its performance. A learning module for self-parameterization of Meta-heuristics (MH) in a Multi-Agent System (MAS) for resolution of scheduling problems is proposed in this work. The learning module is based on Case-based Reasoning (CBR) and two d