首页|基于混合智能优化算法的输变电工程全环节关键数据处理方法

基于混合智能优化算法的输变电工程全环节关键数据处理方法

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
为了提升输变电工程全环节的数据管理质效,提出了一种基于混合智能优化算法的输变电工程全环节关键数据处理方法.该方法以造价数据管理为核心,利用层次分析法建立工程造价控制评估模型,获得了造价评估指标与指标权重.同时设计了一种改进的随机邻域嵌入算法实现数据降维,进而引入经自适应改进的鲸鱼优化算法及粒子群算法.在交叉策略框架下,将两者相结合并得到鲸鱼粒子群混合优化算法.实验结果表明,所提方法对输变电工程全环节关键数据的处理效果较优,而与其他方法相比,其精度和效率也均具备显著优势,能够提升数据管理水平.
Key data processing method based on hybrid intelligent optimization algorithm for full link of power transmission and transformation project
In order to improve the quality and efficiency of data management for the full link of power transmission and transformation project,a key data processing method based on hybrid intelligent optimization algorithm for the full link of power transmission and transformation project was proposed.The cost data management was taken as the core,the engineering cost control assessment model using hierarchical analysis was established,and cost assessment indexes and index weights were obtained.Meanwhile,an improved random neighborhood embedding algorithm was designed to realize data dimensionality reduction,and an adaptively improved whale optimization algorithm and a particle swarm algorithm were introduced.Under the framework of crossover strategy,two algorithms were combined to formulate a hybrid whale particle swarm optimization algorithm.The experimental results show that the as-proposed method is better for the key data processing of the full link of transmission and transformation project,and its accuracy and efficiency have significant advantages over other methods and can improve the data management level.

transmission and transformation projectfull linkhybrid whale particle swarm optimization algorithmrandom neighbourhood embedding algorithmengineering costkey datacrossover strategydata managementhierarchical analysis method

何琳、黄博、申亚波、李爽

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新疆电力有限公司 经济技术研究院,新疆 乌鲁木齐 830063

输变电工程 全环节 鲸鱼粒子群混合优化算法 随机邻域嵌入算法 工程造价 关键数据 交叉策略 数据管理 层次分析法

新疆维吾尔自治区科技计划

Z2020CRDT2D6053

2024

10.7688/j.issn.1000-1646.2024.03.04

沈阳工业大学学报
沈阳工业大学

沈阳工业大学学报

CSTPCD北大核心
影响因子：0.62
ISSN：1000-1646
年,卷(期)：2024.46(3)
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