A Deep Learning Framework for Short-term Power Load Forecasting. - Tinghui Ouyang; Yusen He; Huajin Li; Zhiyu Sun; Stephen Baek (CoRR, 2017)

Record linkage based on a three-way decision with the use of granular descriptors. - Tinghui Ouyang; Witold Pedrycz; Nick J. Pizzi (Expert Syst. Appl., 2019)

Quantitative Analysis of Gas Phase IR Spectra Based on Extreme Learning Machine Regression Model. - Tinghui Ouyang; Chongwu Wang; Zhangjun Yu; Robert Stach; Boris Mizaikoff; Bo Liedberg; Guang-Bin Huang; Qi-Jie Wang (Sensors, 2019)

Monitoring Wind Turbines' Unhealthy Status: A Data-Driven Approach. - Tinghui Ouyang; Yusen He; Heming Huang (IEEE Trans. Emerg. Top. Comput. Intell., 2019)

Modeling and Forecasting Short-Term Power Load With Copula Model and Deep Belief Network. - Tinghui Ouyang; Yusen He; Huajin Li; Zhiyu Sun; Stephen Baek (IEEE Trans. Emerg. Top. Comput. Intell., 2019)

Hybrid Ensemble Framework for Short-Term Wind Speed Forecasting. - Zhenhao Tang; Gengnan Zhao; Gong Wang; Tinghui Ouyang (IEEE Access, 2020)

Cooperative Comfortable-Driving at Signalized Intersections for Connected and Automated Vehicles. - Xun Shen; Xingguo Zhang; Tinghui Ouyang; Yuanchao Li; Pongsathorn Raksincharoensak (IEEE Robotics Autom. Lett., 2020)

AI robustness analysis with consideration of corner cases. - Tinghui Ouyang; Yoshinao Isobe; Vicent Sanz Marco; Jun Ogata; Yoshiki Seo; Yutaka Oiwa (AITest, 2021)

Corner Case Data Description and Detection. - Tinghui Ouyang; Vicent Sanz Marco; Yoshinao Isobe; Hideki Asoh; Yutaka Oiwa; Yoshiki Seo (WAIN@ICSE, 2021)

Corner case data description and detection. - Tinghui Ouyang; Vicent Sant Marco; Yoshinao Isobe; Hideki Asoh; Yutaka Oiwa; Yoshiki Seo (CoRR, 2021)

Randomized Computation for the Current Stress Policy Design in the DAB Converter. - Xun Shen; Tinghui Ouyang; Zhengxi Chen; Shuang Zhao; Jiaxin Fang; Yahui Zhang (IEEE Control. Syst. Lett., 2021)

Feature learning for stacked ELM via low-rank matrix factorization. - Tinghui Ouyang (Neurocomputing, 2021)

Rule-Based Modeling With DBSCAN-Based Information Granules. - Tinghui Ouyang; Witold Pedrycz; Nick J. Pizzi (IEEE Trans. Cybern., 2021)

Granular Description of Data Structures: A Two-Phase Design. - Tinghui Ouyang; Witold Pedrycz; Orion Fausto Reyes-Galaviz; Nick J. Pizzi (IEEE Trans. Cybern., 2021)

NOx Measurements in Vehicle Exhaust Using Advanced Deep ELM Networks. - Tinghui Ouyang; Chongwu Wang; Zhangjun Yu; Robert Stach; Boris Mizaikoff; Guang-Bin Huang; Qi-Jie Wang (IEEE Trans. Instrum. Meas., 2021)

Quality assurance study with mismatched data in sentiment analysis. - Tinghui Ouyang; Yoshiki Seo; Yutaka Oiwa (APSEC, 2022)

Autonomous driving quality assurance with data uncertainty analysis. - Tinghui Ouyang; Yoshinao Isobe; Saïma Sultana; Yoshiki Seo; Yutaka Oiwa (IJCNN, 2022)

Representation learning based on hybrid polynomial approximated extreme learning machine. - Tinghui Ouyang; Xun Shen (Appl. Intell., 2022)

Structural rule-based modeling with granular computing. - Tinghui Ouyang (Appl. Soft Comput., 2022)

Auto-Encoder-Extreme Learning Machine Model for Boiler NOx Emission Concentration Prediction. - Zhenhao Tang; Shikui Wang; Xiangying Chai; Shengxian Cao; Tinghui Ouyang; Yang Li 011 (CoRR, 2022)

Online structural clustering based on DBSCAN extension with granular descriptors. - Tinghui Ouyang; Xun Shen (Inf. Sci., 2022)

DBSCAN-based granular descriptors for rule-based modeling. - Tinghui Ouyang; Xinhui Zhang (Soft Comput., 2022)

Approximate Confidence Region of State Prediction in Stochastic Dynamical Discrete-Time Systems. - Xun Shen; Tinghui Ouyang; Yuhu Wu (ACC, 2023)

A Novel Statistical Measure for Out-of-Distribution Detection in Data Quality Assurance. - Tinghui Ouyang; Isao Echizen; Yoshiki Seo (APSEC, 2023)

Quality Assurance of A GPT-Based Sentiment Analysis System: Adversarial Review Data Generation and Detection. - Tinghui Ouyang; Hoang-Quoc Nguyen-Son; Huy H. Nguyen; Isao Echizen; Yoshiki Seo (APSEC, 2023)

Computing Probabilistic Bounds on State Trajectories for Uncertain Systems. - Xun Shen; Tinghui Ouyang; Yahui Zhang; Xingguo Zhang (IEEE Trans. Emerg. Top. Comput. Intell., 2023)

Sample-Based Neural Approximation Approach for Probabilistic Constrained Programs. - Xun Shen; Tinghui Ouyang; Nan Yang; Jiancang Zhuang (IEEE Trans. Neural Networks Learn. Syst., 2023)

Fuzzy rule-based anomaly detectors construction via information granulation. - Tinghui Ouyang; Xinhui Zhang (Inf. Sci., 2023)

Textual Out-of-Distribution Data Detection Based on Granular Dictionary. - Tinghui Ouyang; Toshiyuki Amagasa (IEEE Big Data, 2024)

Neural architecture search via similarity adaptive guidance. - Yu Xue 003; Jiajie Zha; Mohamed Wahib; Tinghui Ouyang; Xiao Wang 004 (Appl. Soft Comput., 2024)

Stability Analysis of ChatGPT-based Sentiment Analysis in AI Quality Assurance. - Tinghui Ouyang; AprilPyone MaungMaung; Koichi Konishi; Yoshiki Seo; Isao Echizen (CoRR, 2024)

Direction-aware convolutional autoencoder based on positional encoding for one-dimensional anomaly detection. - Qien Yu; Qiong Chang; Tinghui Ouyang; Takio Kurita; Ran Dong (Inf. Sci., 2025)

Textual out-of-distribution (OOD) detection for LLM quality assurance. - Tinghui Ouyang; Yoshiki Seo; Isao Echizen (Knowl. Based Syst., 2025)

Sample-Based Continuous Approximate Method for Constructing Interval Neural Network. - Xun Shen; Tinghui Ouyang; Kazumune Hashimoto; Yuhu Wu (IEEE Trans. Neural Networks Learn. Syst., 2025)