Jinliang Ding
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View article: Visualization of Industrial Big Data: State-of-the-Art and Future Perspectives
Visualization of Industrial Big Data: State-of-the-Art and Future Perspectives Open
View article: Why individuals with trait anger and revenge motivation are more likely to engage in cyberbullying perpetration? The online disinhibition effect
Why individuals with trait anger and revenge motivation are more likely to engage in cyberbullying perpetration? The online disinhibition effect Open
Background Trait anger has been identified as a significant risk factor in cyberbullying perpetration; however, the mechanisms underlying this relationship remain underexplored. This study aims to elucidate the connection between trait ang…
View article: Development and validation of attitudes toward inclusive education scale among Chinese normal universities students’ attitudes
Development and validation of attitudes toward inclusive education scale among Chinese normal universities students’ attitudes Open
View article: Reduced Network Cumulative Constraint Violation for Distributed Bandit Convex Optimization under Slater Condition
Reduced Network Cumulative Constraint Violation for Distributed Bandit Convex Optimization under Slater Condition Open
This paper studies the distributed bandit convex optimization problem with time-varying inequality constraints, where the goal is to minimize network regret and cumulative constraint violation. To calculate network cumulative constraint vi…
View article: MBL-CPDP: A Multi-objective Bilevel Method for Cross-Project Defect Prediction via Automated Machine Learning
MBL-CPDP: A Multi-objective Bilevel Method for Cross-Project Defect Prediction via Automated Machine Learning Open
Cross-project defect prediction (CPDP) leverages machine learning (ML) techniques to proactively identify software defects, especially where project-specific data is scarce. However, developing a robust ML pipeline with optimal hyperparame…
View article: Hierarchical learning control for autonomous robots inspired by central nervous system
Hierarchical learning control for autonomous robots inspired by central nervous system Open
Mammals can generate autonomous behaviors in various complex environments through the coordination and interaction of activities at different levels of their central nervous system. In this paper, we propose a novel hierarchical learning c…
View article: ConGCNet: Convex geometric constructive neural network for Industrial Internet of Things
ConGCNet: Convex geometric constructive neural network for Industrial Internet of Things Open
The intersection of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) has garnered ever-increasing attention and research interest. Nevertheless, the dilemma between the strict resource-constrained nature of IIoT de…
View article: Inside back cover
Inside back cover Open
View article: Interactive visual analytics-based diagnosis and traceback of shape quality anomalies in multi-category heavy plates
Interactive visual analytics-based diagnosis and traceback of shape quality anomalies in multi-category heavy plates Open
厚板的板形质量对于产品的使用性能和市场竞争力至关重要. 由于厚板生产过程的复杂性和生产数据的高维、多源、异构以及规模大等特征, 有效地分析诊断板形质量的异常及其原因是一项极具挑战性的任务. 采用数据可视化与人机交互技术, 本文提出了一种基于交互式可视分析的多规格厚板板形质量异常诊断与回溯方法及系统. 以多视角、多层次的数据呈现方式, 为用户提供了一个直观且深入的工业大数据数据分析探索环境, 能够通过人机交互协助快速识别板型质量异常, 并分析生产过程数据与板形质量变化的内在关…
View article: A Central Motor System Inspired Pre-training Reinforcement Learning for Robotic Control
A Central Motor System Inspired Pre-training Reinforcement Learning for Robotic Control Open
The development of intelligent robots requires control policies that can handle dynamic environments and evolving tasks. Pre-training reinforcement learning has emerged as an effective approach to address these demands by enabling robots t…
View article: Latent Space Inference For Spatial Transcriptomics
Latent Space Inference For Spatial Transcriptomics Open
In order to understand the complexities of cellular biology, researchers are interested in two important metrics: the genetic expression information of cells and their spatial coordinates within a tissue sample. However, state-of-the art m…
View article: Solving Expensive Optimization Problems in Dynamic Environments with Meta-learning
Solving Expensive Optimization Problems in Dynamic Environments with Meta-learning Open
Dynamic environments pose great challenges for expensive optimization problems, as the objective functions of these problems change over time and thus require remarkable computational resources to track the optimal solutions. Although data…
View article: Addressing Domain Shift via Knowledge Space Sharing for Generalized Zero-Shot Industrial Fault Diagnosis
Addressing Domain Shift via Knowledge Space Sharing for Generalized Zero-Shot Industrial Fault Diagnosis Open
Fault diagnosis is a critical aspect of industrial safety, and supervised industrial fault diagnosis has been extensively researched. However, obtaining fault samples of all categories for model training can be challenging due to cost and …
View article: A Novel Multi-dimensional Time-series Data Anomaly Detection Model Based on Generative Adversarial Network Aided Autoencoder
A Novel Multi-dimensional Time-series Data Anomaly Detection Model Based on Generative Adversarial Network Aided Autoencoder Open
With increasing amount and easiness of access the data in industrial processes, data-driven technologies have become more prevalent in process monitoring. Anomaly detection is an indispensable part of process monitoring. However, most indu…
View article: An effective zero-shot learning approach for intelligent fault detection using 1D CNN
An effective zero-shot learning approach for intelligent fault detection using 1D CNN Open
Data-driven fault detection techniques have attracted extensive attention in engineering, industry and many other areas in recent years. In many real applications, the following situation often occurs: data for certain types of faults (uns…
View article: Correction to: Evolutionary optimization of large complex problems
Correction to: Evolutionary optimization of large complex problems Open
The sixth paper included in the special issue is entitled "Surrogate-assisted evolutionary algorithm for expensive constrained multi-objective discrete optimization problems" authored by Q. Gu et al., which proposes a random forestassisted…
View article: Evolutionary optimization of large complex problems
Evolutionary optimization of large complex problems Open
Many real-world applications, such as industrial manufacturing systems and water distribution networks, are complex systems, which may be hard to describe with explicit mathematical models.These are commonly labeled as black-box problems.D…
View article: Thematic issue on knowledge and data driven evolutionary multi-objective optimization
Thematic issue on knowledge and data driven evolutionary multi-objective optimization Open
View article: Contrastive Learning Assisted-Alignment for Partial Domain Adaptation
Contrastive Learning Assisted-Alignment for Partial Domain Adaptation Open
This work addresses unsupervised partial domain adaptation (PDA), in which classes in the target domain are a subset of the source domain. The key challenges of PDA are how to leverage source samples in the shared classes to promote positi…
View article: Guest Editorial: Industrial Artificial Intelligence for Smart Manufacturing
Guest Editorial: Industrial Artificial Intelligence for Smart Manufacturing Open
This Special Section presents the latest developments on intelligent modeling, neural networks, deep learning, and adaptive estimation, and their applications in industrial applications. Through a rigorous peer-review process, eleven artic…
View article: Incremental Data-driven Optimization of Complex Systems in Nonstationary Environments
Incremental Data-driven Optimization of Complex Systems in Nonstationary Environments Open
Existing work on data-driven optimization focuses on problems in static environments, but little attention has been paid to problems in dynamic environments. This paper proposes a data-driven optimization algorithm to deal with the challen…
View article: iHPPVis: Interactive Visual Analysis of Industrial data in Heavy Plate Production
iHPPVis: Interactive Visual Analysis of Industrial data in Heavy Plate Production Open
This paper develops an interactive visualization system, called iHPPVis, to analyze and locate the cause of quality-related faults for the heavy plates production. A time distribution of the products under different operating conditions ba…
View article: A Novel Evolutionary Algorithm for Dynamic Constrained Multiobjective Optimization Problems
A Novel Evolutionary Algorithm for Dynamic Constrained Multiobjective Optimization Problems Open
To promote research on dynamic constrained multiobjective optimization, we first propose a group of generic test problems with challenging characteristics, including different modes of the true Pareto front (e.g., convexity-concavity and c…
View article: Constrained Operational Optimization of a Distillation Unit in Refineries With Varying Feedstock Properties
Constrained Operational Optimization of a Distillation Unit in Refineries With Varying Feedstock Properties Open
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
View article: Incremental data-driven optimization of complex systems in nonstationary environments
Incremental data-driven optimization of complex systems in nonstationary environments Open
View article: Application and Dynamic Simulation of Improved Genetic Algorithm in Production Workshop Scheduling
Application and Dynamic Simulation of Improved Genetic Algorithm in Production Workshop Scheduling Open
From the point of view of combining theories with practice, in order to better realize the effective management of production workshop scheduling and thus improve the competitiveness of manufacturing enterprises in the market, this study f…
View article: Ensemble Random Weights Neural Network based Online Prediction Model of the Production Rate for Mineral Beneficiation Process
Ensemble Random Weights Neural Network based Online Prediction Model of the Production Rate for Mineral Beneficiation Process Open
Mineral beneficiation process consists of a series of unit processes, and it is of great significance to build the relationship between the technical indexes of each unit and the global production index. In this paper, we propose a novel o…
View article: Online Learning Algorithm for LSSVM Based Modeling with Time-varying Kernels
Online Learning Algorithm for LSSVM Based Modeling with Time-varying Kernels Open
Online learning based Least Squares Support Vector Machine (LSSVM) can address the modeling problems of a time-varying process, which has a few advantages such as low training time and good general. Nevertheless, many of online learning al…
View article: Prediction of Physical Properties of Crude Oil Based on Ensemble Random Weights Neural Network
Prediction of Physical Properties of Crude Oil Based on Ensemble Random Weights Neural Network Open
Prediction of physical properties of crude oil plays a key role in the petroleum refining industry, therefore, it is of great significance to establish the prediction model of physical properties of crude oil. In this paper, we propose an …
View article: A Modified Dynamic PLS for Quality Related Monitoring of Fractionation Processes
A Modified Dynamic PLS for Quality Related Monitoring of Fractionation Processes Open
The fractionation process is a typical dynamic process, and practitioners highly pay attention to the quality-related abnormal in the real refining processes. In this paper, a modified dynamic PLS (MDPLS) modeling method and the correspond…