基于阈值选择策略的改进混合蛙跳算法在电网规划中的应用探究
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摘要
结合前人理论了解到传统混合蛙跳算法的优缺点,针对其中缺点进行改善,形成一种更加贴合电网规划的一种阈值选择策略改进混合蛙跳算法。在理论当中,传统的混合蛙跳算法具有计算性能优异,可以对全局进行高效、高速、高准确率搜索,所以此方法的出现受到了许多专业领域的推崇,而在之后的应用当中,混合蛙跳算法暴露出许多缺陷,即该算法的适用性受限于连续性问题条件,在其他问题条件当中,其应用效果并不理想,同时在一些应用过程当中,还很容易陷入局部最优解的问题,因此为了能够将该方法应用到电网规划当中,本文将算法解向量进行离散化处理,同时结合阈值选择策略,得出一种基于阈值选择策略的改进混合蛙跳算法。
Combined with the previous theory to understand the advantages and disadvantages of the traditional hybrid frog leaping algorithm,and to improve the shortcomings,a threshold selection strategy is formed that is more suitable for power grid planning to improve the hybrid frog leaping algorithm.In theory,the traditional hybrid frog leaping algorithm has excellent computational performance and can perform high-efficiency,high-speed,high-accuracy search on the whole.Therefore,the emergence of this method has been highly praised by many professional fields,and in later applications,mixed frogs The hopping algorithm exposes many defects,which is the applicability of the algorithm is limited by the continuity problem condition.In other conditions,the application effect is not good,and in some application processes,it is easy to fall into the local optimal solution.In order to apply the method to grid planning,the algorithm solution vector is discretized and the threshold selection strategy is combined to obtain an improved hybrid leapfrog algorithm.
Combined with the previous theory to understand the advantages and disadvantages of the traditional hybrid frog leaping algorithm,and to improve the shortcomings,a threshold selection strategy is formed that is more suitable for power grid planning to improve the hybrid frog leaping algorithm.In theory,the traditional hybrid frog leaping algorithm has excellent computational performance and can perform high-efficiency,high-speed,high-accuracy search on the whole.Therefore,the emergence of this method has been highly praised by many professional fields,and in later applications,mixed frogs The hopping algorithm exposes many defects,which is the applicability of the algorithm is limited by the continuity problem condition.In other conditions,the application effect is not good,and in some application processes,it is easy to fall into the local optimal solution.In order to apply the method to grid planning,the algorithm solution vector is discretized and the threshold selection strategy is combined to obtain an improved hybrid leapfrog algorithm.
引文
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[4] 高建兴.混合蛙跳算法应用研究[J].网络安全技术与应用,2014,(7):28-29.
[5] 王安龙,何建华,张越,等.基于伪差分扰动的混合蛙跳算法研究[J].计算机应用研究,2014,31(9):2681-2684.
[6] 王文发,许淳,尹斌斌,等.基于改进混合蛙跳算法的动态环境路径规划[J].吉林大学学报(理学版),2016,54(4):857-861.
[7] 魏萍,范红.基于改进的混合蛙跳算法机器人路径规划的研究[J].工业控制计算机,2015,(7):40-41.
[8] 潘桂彬,潘丰,刘国栋.基于改进混合蛙跳算法的移动机器人路径规划[J].计算机应用,2014,34(10):2850-2853.
[9] 潘翔,唐春晖,张仁杰.基于混合蛙跳算法的移动机器人路径规划[J].电子科技,2015,28(11):29.
[10] 徐晓晴,朱庆保.基于蛙跳算法的新型机器人路径规划算法[J].小型微型计算机系统,2014,35(7):1631-1635.
[11] 李玺,窦硕鹏,王海洁.混合蛙跳移动机器人路径规划算法[J].电子制作,2015,(4z):27-28.
[12] 刘海博,刘检华,何永熹,等.基于小生境粒子群算法的公差多目标优化设计[J].计算机集成制造系统,2015,21(3):585-592.
[13] 李琳,张栋栋,沙林秀,等.基于粒子群算法的钻进参数多目标优化[J].现代电子技术,2014,(10):24-27.
[14] 马草原,孙展展,尹志超,等.基于双重混合粒子群算法的配电网重构[J].电工技术学报,2016,31(11):120-128.
[15] 唐贤伦,程祥,汪斌全.采用多Agent混沌粒子群算法的配电网重构[J].电力系统及其自动化学报,2015,27(3):17-23.
[16] 殷豪,李德强,孟安波,等.纵横交叉和粒子群混合算法在配电网重构中的应用[J].电气应用,2015,(22):19-24.