Search Results - "Ouyang, Tinghui"

Fuzzy rule-based anomaly detectors construction via information granulation by Ouyang, Tinghui, Zhang, Xinhui

“…•An advanced anomaly detection method via granular computing is proposed;•Granular data descriptors are used to construct anomaly detectors;•A fuzzy rule-based…”
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Representation learning based on hybrid polynomial approximated extreme learning machine by Ouyang, Tinghui, Shen, Xun

“…As an effective algorithm in feature learning, autoencoder (AE) and its variants have been widely applied in machine learning. To overcome the expensive time…”
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A combined multivariate model for wind power prediction by Ouyang, Tinghui, Zha, Xiaoming, Qin, Liang

“…•A combined multivariate model is proposed for improving prediction accuracy.•Two-stages approach is used to reflect variables’ influence on wind process.•More…”
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A wind turbine bearing fault diagnosis method based on fused depth features in time–frequency​ domain by Tang, Zhenhao, Wang, Mengjiao, Ouyang, Tinghui, Che, Fei

“…Diagnosis of bearing faults has significant meaning to the maintenance of wind turbines in real industry. Well-performed bearing fault diagnosis generally…”
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Granular Description of Uncertain Data for Classification Rules in Three-Way Decision by Zhang, Xinhui, Ouyang, Tinghui

“…Considering that data quality and model confidence bring threats to the confidence of decision-making, a three-way decision with uncertain data description is…”
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Model of selecting prediction window in ramps forecasting by Ouyang, Tinghui, Zha, Xiaoming, Qin, Liang, Xiong, Yi, Huang, Heming

“…Prediction of wind power ramp events is important to the stability operation of power system, it is realized by combining wind power prediction of several…”
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Extension of DBSCAN in Online Clustering: An Approach Based on Three-Layer Granular Models by Zhang, Xinhui, Shen, Xun, Ouyang, Tinghui

“…In big data analysis, conventional clustering algorithms have limitations to deal with nonlinear spatial datasets, e.g., low accuracy and high computation…”
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Granular Description of Data Structures: A Two-Phase Design by Ouyang, Tinghui, Pedrycz, Witold, Reyes-Galaviz, Orion F., Pizzi, Nick J.

“…The study is concerned with a description of large numeric data with the aid of building a limited collection of representative information granules with the…”
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Hybrid Ensemble Framework for Short-Term Wind Speed Forecasting by Tang, Zhenhao, Zhao, Gengnan, Wang, Gong, Ouyang, Tinghui

“…A novel hybrid ensemble framework is developed to forecast the short-term wind speed, which consists of a data preprocessing technique, data-driven based…”
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Sequential Detection of Microgrid Bad Data via a Data-Driven Approach Combining Online Machine Learning With Statistical Analysis by Huang, Heming, Liu, Fei, Ouyang, Tinghui, Zha, Xiaoming

“…Bad data is required to be detected and removed from the microgrid data stream because it misleads the decision-making of the Energy Management Systems (EMS)…”
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Data-driven modeling of truck engine exhaust valve failures: A case study by He, Yusen, Kusiak, Andrew, Ouyang, Tinghui, Teng, Wei

“…Exhaust valve is an essential part of truck engine. Dynamic and unpredictable thermal and mechanical stress cause valves to wear prematurely, leading to…”
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Editorial: Advanced Anomaly Detection Technologies and Applications in Energy Systems by Ouyang, Tinghui, Shen, Xun, He, Yusen, Tang, Zhenhao, Zhang, Yahui

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Improved Surprise Adequacy Tools for Corner Case Data Description and Detection by Ouyang, Tinghui, Marco, Vicent Sanz, Isobe, Yoshinao, Asoh, Hideki, Oiwa, Yutaka, Seo, Yoshiki

“…Facing the increasing quantity of AI models applications, especially in life- and property-related fields, it is crucial for designers to construct safety- and…”
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Robust Bad Data Detection Method for Microgrid Using Improved ELM and DBSCAN Algorithm by Huang, Heming, Liu, Fei, Zha, Xiaoming, Xiong, Xiaoqi, Ouyang, Tinghui, Liu, Wenjun, Huang, Meng

“…AbstractBad data must be detected in the microgrid because they mislead the decision making of energy management systems (EMSs). The authors propose a robust…”
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Feature learning for stacked ELM via low-rank matrix factorization by Ouyang, Tinghui

“…•A improved ELM-based auto-encoder is proposed for effective feature learning.•Low-rank matrix factorization is applied to learn optimal hidden features.•The…”
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Structural rule-based modeling with granular computing by Ouyang, Tinghui

“…In order to analyze the dynamic behaviors of complex systems in the era of big data, a new rule-based modeling approach is proposed in this paper. This…”
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Data-driven modeling of truck engine exhaust valve failures: A case study by He, Yusen, Kusiak, Andrew, Ouyang, Tinghui, Teng, Wei

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Advanced wind power prediction based on data-driven error correction by Yan, Jing, Ouyang, Tinghui

“…•A two-phases hybrid model is proposed for wind power prediction.•Wind power curve is used to obtain trend of wind power primarily.•Errors of the primary model…”
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Online structural clustering based on DBSCAN extension with granular descriptors by Ouyang, Tinghui, Shen, Xun

“…•An DBSCAN extension for online structural clustering is proposed.•Information granules are constructed to describe structures of shaped clusters.•Granular…”
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Two-phase deep learning model for short-term wind direction forecasting by Tang, Zhenhao, Zhao, Gengnan, Ouyang, Tinghui

“…Accurate and reliable wind direction prediction is important for improving wind power conversion efficiency and operation safety. In this paper, a two-phase…”
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