Blar i Publikasjoner fra Cristin på forfatter "Zhang, Jianhua"
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Automatic Analysis of Large-scale Nanopore Data Using Hidden Markov Models
Zhang, Jianhua; Liu, Xiuling (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2020-04-14)In this paper we developed a modified Hidden Markov Model (HMM) to analyze the raw nanopore experimental data. Traditionally, prior to further analysis the measured nanopore data must be pre-filtered, but the filtering ... -
Classifying Mental Workload Levels Using Semi-Supervised Learning Technique
Zhang, Jianhua; Li, Jianrong (IFAC-PapersOnLine;Volume 53, Issue 2, Peer reviewed; Journal article, 2021-04-14)Real-time monitoring and analysis of human operator’s mental workload (MWL) is crucial for development of adaptive/intelligent human-machine cooperative systems in various safety/mission-critical application fields. Although ... -
Cross-Subject emotion recognition from EEG using Convolutional Neural Networks
Zhong, Xiaolong; Yin, Zhong; Zhang, Jianhua (Chinese Control Conference (CCC);2020 39th Chinese Control Conference (CCC), Peer reviewed; Journal article, 2020-09-09)Using electroencephalogram (EEG) signals for emotion detection has aroused widespread research concern. However, across subjects emotional recognition has become an insurmountable gap which researchers cannot step across ... -
EEG-based affect classification with machine learning algorithms
Zhang, Jianhua; Yin, Zhong; Chen, Peng (Chapter, 2023)In this paper, we aim to study the EEG-based emotion recognition problem. First, we use clustering algorithm to determine the target class of emotions and perform binary classification of emotion along its arousal and ... -
An ELM-based Deep SDAE Ensemble for Inter-Subject Cognitive Workload Estimation with Physiological Signals
Zheng, Zhanpeng; Yin, Zhong; Zhang, Jianhua (Chinese Control Conference (CCC);2020 39th Chinese Control Conference (CCC), Conference object, 2020-09-09)Evaluating operator cognitive workload (CW) levels in human-machine systems based on neurophysiological signals is becoming the basis to prevent serious accidents due to abnormal state of human operators. This study proposes ... -
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
Zhang, Jianhua; Yin, Zhong; Chen, Peng; Nichele, Stefano (Information Fusion;Volume 59, July 2020, Peer reviewed; Journal article, 2020-01-31)In recent years, the rapid advances in machine learning (ML) and information fusion has made it possible to endow machines/computers with the ability of emotion understanding, recognition, and analysis. Emotion recognition ... -
Hierarchical MPC of Hybrid Power Systems based on Fuzzy Discrete Abstraction
Zhang, Jianhua; Xia, Jiajun (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2020-04-14)A hierarchical control approach is proposed for hybrid systems with discrete-valued input based on fuzzy discrete abstraction and model predictive control (MPC) scheme. The system is firstly abstracted to a discrete event ... -
Household Energy Consumption Prediction: A Deep Neuroevolution Approach
Soudaei, Alexander; Zhang, Jianhua; Elmi, Mohamed Ahmed; Tsechoev, Mikael; Khan, Zishan; Osman, Ahmed Abbas (Chapter, 2023)Accurate energy consumption prediction can provide insights to make better informed decisions on energy purchase and generation. It also can prevent overloading and make it possible to store energy more efficiently. In ... -
Instantaneous mental workload assessment using time–frequency analysis and semi-supervised learning
Zhang, Jianhua; Li, Jianrong; Wang, Rubin (Cognitive Neurodynamics;volume 14, issue 5, Peer reviewed; Journal article, 2020-05-12)The real-time assessment of mental workload (MWL) is critical for development of intelligent human–machine cooper- ative systems in various safety–critical applications. Although data-driven machine learning (ML) approach ... -
Manifold feature fusion with dynamical feature selection for cross-subject emotion recognition
Hua, Yue; Zhong, Xiaolong; Zhang, Bingxue; Yin, Zhong; Zhang, Jianhua (Brain Sciences;Volume 11 / Issue 11, Peer reviewed; Journal article, 2021-10-23)Affective computing systems can decode cortical activities to facilitate emotional human– computer interaction. However, personalities exist in neurophysiological responses among different users of the brain–computer ... -
Operator Performance Prediction based on Fuzzy Modeling Approach
Zhang, Jianhua; Yin, Zhong (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2021-04-14)In this paper, physiological signals were measured from five participants, each participating in two sessions of experiment with identical experimental procedure. A simulation platform, AutoCAMS (Automation-enhanced Cabin ... -
Prediction and correlation analysis of ventilation performance in a residential building using artificial neural network models based on data-driven analysis
Kim, Moon Keun; Cremers, Bart; Liu, Jiying; Zhang, Jianhua; Wang, Junqi (Sustainable Cities and Society (SCS);Volume 83, August 2022, 103981, Peer reviewed; Journal article, 2022-06-14)This study investigates approaches to evaluate prediction and correlation how significantly mechanical and natural ventilation rate and local weather conditions affect the actual ventilation performance of a residential ... -
Recognition of cognitive load with a stacking network ensemble of denoising autoencoders and abstracted neurophysiological features
Cao, Zixuan; Yin, Zhong; Zhang, Jianhua (Peer reviewed; Journal article, 2020) -
Selection of Optimal EEG Electrodes for Human Emotion Recognition
Zhang, Jianhua; Chen, Peng (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2021-04-14)In recent years, emotion recognition has attracted increasing interest from researchers from diverse fields. Because of their intrinsic correlation with emotions, physiological signals based emotion recognition method is ...