基于离散天牛群算法的高桩码头传感器优化布置
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Sensor optimal placement of high piled-wharf based on binary beetle-swarm algorithm
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    摘要:

    天牛须搜索(BAS)及其优化算法天牛群(BSO)算法是近两年新兴的一种生物启发式算法,具有易实现、收敛速度快等特点,但其仅适用于连续函数优化问题。目前高桩码头结构健康监测系统中传感器优化布置研究较少、布置方法存在盲目性。针对高桩码头传感器优化布置这一具体的离散问题,采用“0-1”编码的方法,引入位置变换概率的思想和离散化天牛群算法,基于模态置信度准则,提出了一种基于离散天牛群(BBSO)算法的高桩码头传感器优化布置方法。以某高桩码头为例,研究了该方法的应用,并与传统的离散粒子群(BPSO)算法进行了比较。结果表明,该方法比传统的BPSO算法更适合和有效。

    Abstract:

    Binary beetle-swarm (BAS) and its optimization algorithm (BSO) is a new biological heuristic algorithm in recent two years,which is easy to implement and fast in convergence,but it is only suitable for continuous function optimization.At present,there are few researches on the sensor placement optimization in the structural health monitoring system of high piled-wharf,and the placement method is blind.Aiming at the discrete problem of sensor optimal placement of high piled-wharf,this paper adopts the method of “0-1” coding,introduces the idea of position transformation probability,discreting BSO algorithm,and proposes a method of sensor optimal placement of high piled-wharf based on the criterion of modal confidence by BBSO algorithm.Based on the case study of a high piled-wharf,the application of the proposed method is studied and compared with the traditional BPSO algorithm.The results show that the proposed method is more suitable and effective than the traditional BPSO algorithm.

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胥松奇,周世良,曹师宝,等.基于离散天牛群算法的高桩码头传感器优化布置[J].水运工程,2020(6):46-52.

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  • 在线发布日期: 2020-06-08
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