Building energy consumption prediction method based on rough set and deep belief neural network

Abstract

The invention discloses a building energy consumption prediction method based on a rough set and a deep belief neural network. The method comprises the following steps: 1, carrying out the data actualmeasurement of a rough set reduction building energy consumption impact factor, and determining the numerical range of each energy consumption level; 2, performing attribute reduction preprocessing on the building energy consumption influence factors by utilizing the rough set; step 3, carrying out actual measurement on sample data for predicting building energy consumption by using the deep neural network; 4, superposing a restricted Boltzmann machine, and constructing a deep belief neural network to perform learning training on the training sample; and 5, performing building energy consumption prediction by taking the residual important building energy consumption influence factors after attribute reduction as input parameters of the deep belief neural network and building energy consumption as output of the deep belief neural network by utilizing Matlab software. The building energy consumption prediction method solves the problems that a traditional building energy consumption prediction method is insufficient in accuracy and practicability, and a new method is provided for prediction of building energy consumption.

Description

technical field [0001] The invention belongs to the technical field of building energy consumption prediction, and in particular relates to a building energy consumption prediction method based on rough sets and deep confidence neural networks. Background technique [0002] With the rapid development of the global economy, the problem of increased energy consumption is becoming more and more serious. As a form of energy consumption, building energy consumption has now accounted for more than one-third of the total global energy consumption. Therefore, how to reduce building energy consumption to alleviate energy pressure has become particularly important. Improving energy efficiency is an effective means to reduce building energy consumption, and predicting building energy consumption is an important way to improve energy efficiency. Accurate building energy consumption forecasting can help building managers improve building energy demand and supply management, and achieve...

AI Technical Summary

Problems solved by technology

[0004] The present invention aims to provide a more accurate, objective, more effective and practical building energy consumption prediction method based on rough sets and deep confidence neural network to solve the problem of low accuracy of traditional building energy consumption methods and difficulty in applying them to actual situations Technical issues for better and accurate forecasting of building energy consumption

Images