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文章摘要
基于区块链数据安全机制的输变电工程建设动态计算技术研究
Research on dynamic calculation technology of power transmission and transformation construction based on blockchain data security mechanism
Received:April 21, 2021  Revised:May 07, 2021
DOI:10.19753/j.issn1001-1390.2024.07.002
中文关键词: 区块链  数据安全  输变电工程  神经网络
英文关键词: blockchain, data security, power transmission and transformation project, neural network
基金项目:国家电网有限公司科技项目(SGLNSY00HLJS2002775);国家自然科学基金优秀青年基金(62022044)
Author NameAffiliationE-mail
Yan Lei State Grid Liaoning Electric Power Company Limited yanlei19760115@126.com 
Luan Ling* Shenyang Power Supply Company of State Grid Liaoning Electric Power Company Limited Luanling19780225@163.com 
Wu Xiaolin State Grid Liaoning Electric Power Company Limited 37318544@qq.com 
Xie Xiangpeng Nanjing University of Posts and Telecommunications xiexp@njupt.edu.cn 
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中文摘要:
      针对现今输变电工程施工过程中不确定性因素较多、造价计算偏向静态等问题,文章建立了基于区块链数据安全机制的输变电工程造价实时动态计算模型,实现了造价实时动态计算技术与计算结果的精准高效。首先,以区块链可信数据交换技术为底层模型,利用区块链去中心化信任体系、链上数据不可篡改等特性,构建输变电工程的数据上传、交互、储存与计算的架构体系。其次,使用粒子群算法优化径向基神经网络参数,构造输变电工程造价数据预测计算模型。最后,采用杰卡德距离对计算结果进行校正且在反馈误差的同时进一步优化计算模型,并利用仿真算例验证了模型的先进性与可行性。
英文摘要:
      Considering that there are many uncertain factors in the construction process of power transmission and transformation projects and the cost calculation tends to be stationary, a real-time dynamic calculation model of transmission and transformation project cost based on blockchain data security mechanism is established in this paper. The model accomplishes the accuracy and efficiency of the calculation results of power transmission and transformation project cost. First of all, the blockchain trusted data exchange technology is used as the underlying model. Utilizing the decentralized characteristic of blockchain, the immutable characteristic of the chain data and other characteristics, the architecture system of data uploading, interaction, storage and calculation in power transmission and transformation projects is constructed. Secondly, particle swarm optimization algorithm is used to optimize the parameters of RBF neural network and the prediction calculation model of power transmission and transformation project cost data is constructed. Finally, Jaccard distance is used to correct the calculation results and react the error while optimizing the model. The model is verified to be advanced and feasible by simulation examples.
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