Titlebook: Intelligent Computing Theories and Application; 12th International C De-Shuang Huang,Kang-Hyun Jo Conference proceedings 2016 Springer Inte

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Intelligent Computing Theories and Application978-3-319-42294-7Series ISSN 0302-9743 Series E-ISSN 1611-3349

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https://doi.org/10.1007/978-3-319-42294-7biological networks; computer vision; ensemble methods; kernel methods; neural networks; artificial intel

壟斷

inveigh

A Hybrid Scatter Search Algorithm to Solve the Capacitated Arc Routing Problem with Refill Points arcs must be refilled on the spot by using a second vehicle. This problem is addressed in real-world applications in many services systems. The problem consists on simultaneously determining the vehicles routes that minimize the total cost. In the literature is proposed an integer linear programmin

DIS

A Novel Fitness Function Based on Decomposition for Multi-objective Optimization Problemsions is of great importance for multi-objective evolutionary algorithms. To this end, in this paper, a novel fitness function based on decomposition is proposed to help solutions converge toward to the Pareto optimal solutions and maintain the diversity of solutions. First, the objective space is de

牛馬之尿

MREP: Multi-Reference Expression Programmingin a single chromosome. However, when the ratio of genes reuse is low, it may not get a high accuracy result within limited iterations and may fall into the trap of local optimum. Therefore, we proposed a novel genetic evolutionary algorithm named MREP (multi-reference expression programming). The M

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Extraction of Independent Components from Sparse Mixtures a dictionary-learning-like objective function which tries to discover independent atoms and corresponding sparse mixing matrix. The objective function involves fidelity term, L1 normalization term and Negentropy term which respectively limits noise, maximizes the sparseness of mixing matrix and no

拱形大橋

puzzle

A Compressed Sensing Based Feature Extraction Method for Identifying Characteristic Genesm gene expression data. In this paper, a novel compressed sensing (CS) based feature extraction method named CSGS is proposed to identify the characteristic genes. Considering the transposed gene expression matrix and class labels as sensing matrix and measurement vector, respectively, CS reconstruc

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