机电工程技术2024，Vol.53Issue(7)：231-234,314,5.DOI:10.3969/j.issn.1009-9492.2024.07.049
基于机器学习算法的高层建筑电气设备分类
Classification of Electrical Equipment in High-rise Buildings Based on Machine Learning Algorithms
杨光 1陈健 2付宝鑫2
作者信息
- 1. 常州中海电力科技有限公司,江苏常州 213000
- 2. 天津电气科学研究院有限公司,天津 300180
- 折叠
摘要
Abstract
Electrical equipment within high-rise buildings is vulnerable to detrimental consequences resulting from transient power quality disturbances.To identify equipment necessitating protection,it becomes imperative to conduct disturbance tolerance testing.However,the task of efficiently and effectively selecting the appropriate equipment for testing from a wide array of options presents a challenge.This study aims to address this predicament by investigating the implementation of the Naive Bayes algorithm in an electrical equipment classification model specifically tailored to high-rise buildings.The classification process involves categorizing the electrical equipment into four distinct classes based on five features associated with disturbance tolerance.By capitalizing on prior knowledge and utilizing labeled data pertaining to electrical equipment,a classification model is developed specifically for high-rise buildings.The model is subsequently trained and tested using a dataset comprising diverse types of electrical equipment obtained from a specific high-rise building.The accuracy and effectiveness of the classification model are thoroughly evaluated.The findings demonstrate that the proposed Naive Bayes-based electrical equipment classification model achieves commendable performance on the dataset,thereby introducing a fresh research direction and approach for expedited classification of electrical equipment in high-rise buildings.关键词
机器学习/高层建筑/电气设备Key words
machine learning/high-rise building/electric equipment分类
建筑与水利引用本文复制引用
杨光,陈健,付宝鑫..基于机器学习算法的高层建筑电气设备分类[J].机电工程技术,2024,53(7):231-234,314,5.
