Public energy consumption prediction method based on machine learning

A technology of energy consumption and machine learning, applied in machine learning, neural learning methods, forecasting, etc., can solve problems such as lack of effective means, and achieve high service quality, healthy environment, and accurate energy consumption prediction
CN112365082APending Publication Date: 2021-02-12马鞍山学院
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
马鞍山学院
Publication Date
2021-02-12

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Abstract

The invention discloses a public energy consumption prediction method based on machine learning, and belongs to the field of energy consumption prediction. The method comprises the following steps: S101, collecting data; S102, data preprocessing: A, performing outlier elimination by adopting an MAD algorithm; B, replacing the missing value; and C, performing variable reduction by adopting a PCA algorithm; and S103, carrying out prediction modeling; a DNN deep neural network is adopted for calculation, and the DNN and more hidden layers are used together in an R software tool in a Keras libraryby utilizing the collected data. The provided method overcomes the current situation that in the prior art, public energy consumption prediction still lacks effective means, and mainly solves the problem of how to integrate a big data platform and machine learning into an intelligent system for managing energy. Efficiency of a public department is an important component of a smart city concept, and the method is implemented in an existing MERIDA intelligent system and provides accurate energy consumption prediction for users.
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Description

technical field

[0001] The present invention relates to the technical field of energy consumption prediction, and more specifically, to a method for predicting public energy consumption based on machine learning. Background technique

[0002] In the context of smart cities, how to achieve accurate energy consumption of public facilities is an important problem to be solved urgently, because large public buildings are the main energy consumers, especially public buildings with high frequency of use such as education, health, and government. For large buildings, an accurate energy consumption prediction model can effectively provide decision-making basis for energy consumption regulation and energy conservation optimization. However, the latest developments in machine learning in this field, the big data environment has not been fully utilized.

[0003] After searching, the Chinese patent application number: 201811519685.5, and the name of the invention is: an energy consumpt...

Claims

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