| 基于大数据分析的差异化投资增量配电网的效益预测方法研究 |
投稿时间：2019-12-12 修订日期：2020-03-03  点此下载全文 |
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| 中文摘要:配电网的效益具有差异性，为了提高配电网的效益预测水平，提出基于大数据分析的差异化投资增量的配电网效益预测方法。建立差异化投资增量配电网效益评价的指标分析模型，采用大数据分析方法进行差异化投资增量配电网效益分析，结合特征空间重构技术进行差异化投资增量配电网效益的分布式特征序列重组，提取差异化投资增量配电网效益分布特征量，采用关联规则挖掘方法对分布特征量进行效益优先性评价，采用模糊相关检测方法进行配电网效益分布大数据的抗干扰处理，对提取的差异化投资增量配电网效益分布特征量采用神经网络学习方法进行配电网的效益预测，构建效益分布的差异化因子，实现基于大数据分析的差异化投资增量配电网的效益预测。仿真测试结果表明，采用该方法进行差异化投资下的增量配电网效益预测准确性与灵敏度较高，可靠性较好。 |
| 中文关键词:大数据分析 差异化投资 增量配电网 效益预测 |
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| Benefit Prediction of differential Investment incremental Distribution Network based on big data Analysis |
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| Abstract:In order to improve the efficiency prediction level of distribution network, this paper proposes a method of distribution network efficiency prediction based on big data analysis and differential investment increment. This paper establishes the index analysis model of the benefit evaluation of the differential investment incremental distribution network, analyzes the benefit of the differential investment incremental distribution network by using the big data analysis method, recombines the distributed characteristic sequence of the benefit of the differential investment incremental distribution network by combining the characteristic space reconstruction technology, extracts the distribution characteristic quantity of the benefit of the differential investment incremental distribution network, and uses the association rule mining method The distribution characteristic quantity is used for benefit priority evaluation, the fuzzy correlation detection method is used for anti-interference processing of big data of distribution network benefit distribution, the neural network learning method is used for benefit prediction of distribution network for the extracted differential investment increment distribution network benefit distribution characteristic quantity, the differential factor of benefit distribution is constructed, and the differential investment increment based on big data analysis is realized Benefit prediction of distribution network. The simulation test results show that the accuracy, sensitivity and reliability of the incremental distribution network benefit prediction based on this method are high. |
| keywords:Big data analysis differentiation investment incremental distribution network benefit prediction |
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