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Adaptive Ant Colony Algorithm Used in WSNs Routing for Information Acquisition of Manufacturing Process

机译:用于WSNS路由的自适应蚁群算法,以获取制造过程的信息

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Ant colony algorithm (ACA) is employed and improved in routing protocol of information acquisition of manufacturing process based on wireless networks. Weighting factor for paths selection is defined as an exponential variable in adaptive ACA. In this way, it prevents the weighting factor from excess increasing or rapid reducing to 0 which results in local optimum. This approach can dynamically adjust paths selection and improve global search ability by optimizing global policy. Adaptive ACA consumes the least time in the process of searching the most optimized paths and searches the shortest paths under the same of iterative loops. Under the same condition of the information heuristic factor and the expected heuristic factor, the algorithm shows good adaptation, realizes the load balancing between paths and resolves the dynamic adjustment problem.
机译:基于无线网络的制造过程的信息获取的路由协议,采用和改进了蚁群算法(ACA)。路径选择的加权因子被定义为Adaptive ACA中的指数变量。以这种方式,它可以防止加权因子过度增加或快速减少到0,这导致局部最佳。这种方法可以通过优化全局策略来动态调整路径选择并提高全球搜索能力。自适应ACA在搜索最优化的路径的过程中消耗最少的时间,并在相同的迭代循环下搜索最短的路径。在信息启发式因子和预期的启发式因子的同样条件下,算法显示了良好的适应,实现了路径之间的负载平衡并解决了动态调整问题。

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