基于多维KNN算法的电力营销大数据智能分析框架

Yaoyu Wang, Chen Tan, Chengfei Qi, Hongzhang Xiong
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引用次数: 0

摘要

基于多维KNN算法的电力营销大数据智能分析框架是本文研究的重点。通过回顾可以看出,信息挖掘算法需要两个重要参数,即聚类数和权重指标。如果聚类的数量小于聚类样本的总数,则意味着数据挖掘是没有意义的。因此,为了达到设计有效模型的目的,将时间序列和KNN相结合来构建有效模型。电力公司可以通过通用的移动宽带网络连接到不同的供电站,也可以实现高效的营销网络。因此,本文利用这些收集到的数据,进行基于多维度分析的电力营销大数据智能分析框架。通过全面的系统设计,通过高效分析对模型进行评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Analysis Framework of Power Marketing Big Data based on Multi-Dimensional KNN Algorithm
Intelligent analysis framework of power marketing big data based on multi-dimensional KNN algorithm is the main focus of this paper. Through the review, it is evident that the information mining algorithm needs two important parameters, the number of clusters and weight index. If the number of clusters is less than the total number of the clustered samples, it means that the data mining is meaningless. Hence, to achieve the goal of designing an efficient model, the time series and KNN are combined to construct the efficient model. Power companies can connect to the different power supply stations through general mobile broadband networks and also achieve the efficient marketing network. Hence, this paper uses these collected data to conduct smart analysis framework of power marketing big data based on the multi-dimensional analysis. Through the comprehensive systematic design, the model is evaluated through the efficient analysis.
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