Zenan Yang
Hohai University
12 Papers
Zenan Yang is an academic researcher from Hohai University. The author has contributed to research in topics: Computer science & Photovoltaic system. The author has an hindex of 1, co-authored 1 publications.
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Papers
Fault diagnosis approach for photovoltaic array based on the stacked auto-encoder and clustering with I-V curves
TL;DR: A fault diagnosis method is proposed for photovoltaic array based on stacked auto-encoder and clustering algorithm, which can automatically extract features and use a small number of labeled data samples to mine data sample features for fault diagnosis.
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Intelligent fault diagnosis of photovoltaic array based on variable predictive models and I–V curves
Yongjie Liu,Kun Ding,Jingwei Zhang,Ying Hong Lin,Zenan Yang,Xiang Chen,Yuanliang Li,Xihui Chen +7 more
TL;DR: Wang et al. as mentioned in this paper proposed an intelligent fault diagnosis method for photovoltaic arrays based on the variable predictive models and I-V curves, which reduced the computational cost and avoided the problem that the kernel function and hyperparameter are difficult to determine.
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Internet-of-Things-Based Multiple-Sensor Monitoring System for Soil Information Diagnosis Using a Smartphone
Yin Wu,Zenan Yang,Yanyi Liu +2 more
TL;DR: In this paper , a real-time monitoring of soil quality and conditions in wireless multi-sensing based on the Internet of Things (IoT) is presented, which consists of multiple sensors (temperature and moisture), a micro-processor, a microcomputer, a cloud platform, and a mobile phone application.
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Health status evaluation of photovoltaic array based on deep belief network and Hausdorff distance
TL;DR: In this paper , a method for evaluating the health status of photovoltaic arrays based on deep belief network (DBN) and Hausdorff distance (HD) is proposed.
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Fast simulation modeling and multiple-PS fault diagnosis of the PV array based on I–V curve conversion
Hang Yang,Kun Ding,Xiang Chen,Meng Jiang,Zenan Yang,Jingwei Zhang,Ruiguang Gao +6 more
TL;DR: This paper proposes a method for partial shading fault diagnosis in photovoltaic arrays using I-V curve conversion, modeling, and diagnosis, achieving high accuracy in power degradation quantification, PS recognition, and fault severity diagnosis.
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