气候变化领域集成服务门户(CCPortal): Natural Gas Consumption Monitoring Based on k-NN Algorithm and Consumption Prediction Framework Based on Backpropagation Neural Network

CCPortal

DOI	10.3390/buildings14030627
	Natural Gas Consumption Monitoring Based on k-NN Algorithm and Consumption Prediction Framework Based on Backpropagation Neural Network
	Hou, Yaolong; Wang, Xueting; Chang, Han; Dong, Yanan; Zhang, Di; Wei, Chenlin; Lee, Inhee; Yang, Yijun; Liu, Yuanzhao; Zhang, Jipeng
发表日期	2024
EISSN	2075-5309
起始页码	14
结束页码	3
卷号	14 期号:3
英文摘要	With increasing consumption of primary energy and deterioration of the global environment, clean energy sources with large reserves, such as natural gas, have gradually gained a higher proportion of the global energy consumption structure. Monitoring and predicting consumption data play a crucial role in reducing energy waste and improving energy supply efficiency. However, owing to factors such as high monitoring device costs, safety risks associated with device installation, and low efficiency of manual meter reading, monitoring natural gas consumption data at the household level is challenging. Moreover, there is a lack of methods for predicting natural gas consumption at the household level in residential areas, which hinders the provision of accurate services to households and gas companies. Therefore, this study proposes a gas consumption monitoring method based on the K-nearest neighbours (KNN) algorithm. Using households in a residential area in Xi'an as research subjects, the feasibility of this monitoring method was validated, achieving a model recognition accuracy of 100%, indicating the applicability of the KNN algorithm for monitoring natural gas consumption data. In addition, this study proposes a framework for a natural gas consumption prediction system based on a backpropagation (BP) neural network.
英文关键词	energy shortage; instrument monitoring; natural gas consumption; KNN; BP neural network
语种	英语
WOS研究方向	Construction & Building Technology ; Engineering
WOS类目	Construction & Building Technology ; Engineering, Civil
WOS记录号	WOS:001191493100001
来源期刊	BUILDINGS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/296039
作者单位	Xi'an Jiaotong University; Xi'an Jiaotong University; Xi'an Jiaotong University; Pusan National University; Beijing Institute of Technology
推荐引用方式 GB/T 7714	Hou, Yaolong,Wang, Xueting,Chang, Han,et al. Natural Gas Consumption Monitoring Based on k-NN Algorithm and Consumption Prediction Framework Based on Backpropagation Neural Network[J],2024,14(3).
APA	Hou, Yaolong.,Wang, Xueting.,Chang, Han.,Dong, Yanan.,Zhang, Di.,...&Zhang, Jipeng.(2024).Natural Gas Consumption Monitoring Based on k-NN Algorithm and Consumption Prediction Framework Based on Backpropagation Neural Network.BUILDINGS,14(3).
MLA	Hou, Yaolong,et al."Natural Gas Consumption Monitoring Based on k-NN Algorithm and Consumption Prediction Framework Based on Backpropagation Neural Network".BUILDINGS 14.3(2024).