计算机科学
人工智能
故障检测与隔离
人工神经网络
断层(地质)
电力系统
机器学习
功率(物理)
执行机构
量子力学
物理
地质学
地震学
作者
Manojna,Sridhar M. S,Nikhil Nikhil,Anand Kumar,Pratyay Amrit
出处
期刊:2021 2nd International Conference on Smart Electronics and Communication (ICOSEC)
日期:2021-10-07
被引量:1
标识
DOI:10.1109/icosec51865.2021.9591972
摘要
In recent era the need of electricity is increasing but generation and transmission capacity is not increasing at the same rate.The electrical power systems consist of many complex and dynamic elements, which are always prone to disturbance or an electrical fault. This paper is mainly emphasized on the classification of Power faults using machine learning along with artificial neural networks.Three models were considered, and all were analysed with different combinations of input so that the highest accuracy could be achieved. In order to determine the best model and the best combination of input the collected dataset was fed into classification learner app where the app trained the dataset for 24 machine learning models and the model with the highest accuracy is discussed below.
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