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Titlebook: Bio-inspired Computing: Theories and Applications; 9th International Co Linqiang Pan,Gheorghe Păun,Tao Song Conference proceedings 2014 Spr

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楼主: 乳钵
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Real-Coded Genetic Algorithm with Oriented Search towards Promising Region for Parameter Optimizatimization literature is used to test the performance of the proposed real-coded genetic algorithms. Simulations show the proposed approach is a significant evolutionary computing to efficiently solve parameter optimization problems.
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A Population-P-Systems-Inspired Membrane Algorithm for Multi-objective Optimization, obtain well converged and distributed solution set. Moreover, differential evolution is employed as search operator in PPSMA. Twelve multi-objective benchmark problems are utilized to test algorithm performance. Experimental results show that PPSMA performs better than five compared algorithms.
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Worst-Case Execution Time Test Generation for Solutions of the Knapsack Problem Using a Genetic Algroblem, which is often called “the easiest NP-complete problem”. For randomly generated test data, the expected running time of some algorithms for this problem is linear. We present an approach for generation of tests against algorithms for the knapsack problem. This approach is based on genetic al
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The Application of Spiking Neural P Systems for PLC Programming,tems to build a PLC control system model is proposed and implemented through the PLC programming application of a typical water level control system. Example shows that PLC programming process has been simplified and readability of the program has been enhanced after the introduction of SN P systems
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