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Apparatus and method for Deep neural network based power demand prediction

机译:基于深度神经网络的电力需求预测的装置和方法

摘要

A deep neural network-based power demand prediction apparatus and method for predicting power demand by performing pre-processing on missing data, configuring an independent prediction model for each data for prediction, and configuring a prediction model that merges independent prediction models. About. In the deep neural network-based power demand prediction apparatus according to an embodiment of the present invention, a data preprocessor preprocessing data for predicting power demand, and a first prediction model independent for each data using data preprocessed by the data preprocessor. A prediction model generation unit that generates and merges a plurality of first prediction models to generate a second prediction model, and predicts the amount of power demand using the first prediction model and the second prediction model generated by the prediction model generation unit. A prediction that evaluates the effectiveness of the first and second prediction models based on the power demand prediction unit and the prediction accuracy according to the result of preprocessing data by the data preprocessor and the result of predicting the amount of power demand by the power demand prediction unit. Includes an accuracy analysis unit.
机译:基于深度神经网络的功率需求预测装置和方法通过在缺失数据上执行预处理来预测电力需求,为每个数据配置独立的预测模型,以及配置合并独立预测模型的预测模型。关于。在根据本发明实施例的基于深度神经网络的功率需求预测装置中,用于预测用于预测功率需求的数据预处理数据,以及使用由数据预处理器预处理的数据独立于每个数据的第一预测模型。一种预测模型生成单元,其生成和合并多个第一预测模型以生成第二预测模型,并使用由预测模型生成单元生成的第一预测模型和第二预测模型预测电力需求量。根据数据预处理器的预处理数据结果和预测数据的结果,评估第一和第二预测模型的有效性的预测和预测准确性以及通过电力需求预测预测电力需求量的结果单元。包括精度分析单元。

著录项

  • 公开/公告号KR20210026447A

    专利类型

  • 公开/公告日2021-03-10

    原文格式PDF

  • 申请/专利权人 한국전력공사;

    申请/专利号KR1020190107234

  • 申请日2019-08-30

  • 分类号G06Q50/06;G06N3/08;H02J3;

  • 国家 KR

  • 入库时间 2022-08-24 17:36:05

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