Malignant Load Identification of University Dormitory Based on Probabilistic Neural Network
文献类型：会议论文
| 作者 | Qingtian Wu; Tingxin Yan; Yimin Zhou |
| 出版日期 | 2016 |
| 会议名称 | ROBIO2016 |
| 会议地点 | 山东青岛 |
| 英文摘要 | In this paper, a malignant load identification method for the university dormitory is developed based on the improved probabilistic neural network. Firstly, all types of electric loads are numbered and the load code libraries are established. Then the typical electrical parameters such as voltage, current, power, power factor, harmonics, etc are collected within 15 seconds from the starting moment and the nonlinear mapping relationship between the load parameters and type code is developed so as to establish the PNN network. The particle swarm optimization algorithm is studied to optimize the smoothing factor of the PNN, where the optimal smoothing factor can be acquired via particle position and velocity update in the iterative process. The improved PNN is applied to the malignant load identification for college apartments and accurate identification can be achieved so that further action can be taken to avoid fire or other accidents occurrence. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/10088]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2016 |
| 推荐引用方式 GB/T 7714 | Qingtian Wu,Tingxin Yan,Yimin Zhou. Malignant Load Identification of University Dormitory Based on Probabilistic Neural Network[C]. 见:ROBIO2016. 山东青岛. |
入库方式： OAI收割
来源：深圳先进技术研究院
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