Title: Building energy consumption forecasting algorithm based on piecewise linear fusion and exponential spectrum analysis

Authors: Dahui Li; Jianzhao Cui; Yunfei Bai; Chenqiang Zhan

Addresses: School of Computer and Control Engineering, Qiqihar University, 42 Culture Street, Qiqihar, Heilongjiang Province 161000, China ' School of Computer and Control Engineering, Qiqihar University, 42 Culture Street, Qiqihar, Heilongjiang Province 161000, China ' School of Computer and Control Engineering, Qiqihar University, 42 Culture Street, Qiqihar, Heilongjiang Province 161000, China ' School of Computer, Jiangxi University, Nanchang 330031, China

Abstract: In order to solve the problem of large error in traditional statistical prediction methods, a large data prediction method based on pie chart is proposed. Linear fusion and exponential spectrum analysis methods are proposed. The method establishes the target model of building energy consumption prediction and carries out nonlinear exponential sequence analysis. Game analysis of building energy consumption, segmentation linear fusion method is used to decompose the characteristics of building energy consumption map, and statistical analysis is carried out. According to the evolution of feature decomposition and learning trends, the analysis and accurate prediction of building energy consumption big data is realised. The simulation results show that the method reduces energy consumption, is conducive to building energy-saving emission reduction and green building, and provides a new idea for building energy conservation. Provide scientific support for the development of building energy conservation and environmental protection.

Keywords: big data environment; building energy consumption; forecasting algorithm; map feature analysis.

DOI: 10.1504/IJICT.2019.103200

International Journal of Information and Communication Technology, 2019 Vol.15 No.4, pp.357 - 369

Received: 24 Sep 2018
Accepted: 29 Oct 2018
Published online: 22 Oct 2019 *

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