Special Issue on Advances in Industrial Artificial Intelligence (AIAI)
• 大类 : 工程技术 - 2区
• 小类 : 计算机：信息系统 - 1区
In general,Industrial Artificial Intelligence(IAI)refers to the application of artificial intelligence to industrial automation. Different from general artificial intelligence, industrialAInarrows downthe scope ofAIresearch fields to building intelligent systems that resolve engineering problems with human-like intelligence. IndustrialAIstresses more applications rather thanAIconcept or framework development and highlights the value ofAIsolution to specific process industry, including causality identification between input-output variables, state or product quality estimate, retrieval and reasoning of interesting cases, motif discovery from the closed-loop system for monitoring, fault diagnosis and detection, soft-sensing, parameter, structure and process optimization, planning and coordination, dynamical system modelling and control.
IAIhas received sufficiently technical supports from sensing techniques, more powerful computing facilities and stronger communication infrastructure. However, one should be aware that these technologies mentioned above may create some business values only if the problems in industry can be well studied and formulated. Understanding the domain-based AI (DBAI) concept is important and meaningful toAIcommunity, and one cannot expect much ofAItechnologies without knowing the application background in depth, the data nature, and dynamics and constraints of the variables.IAI, as a member ofDBAIfamily, will play a key role in contributing to product and service innovation, process improvement, and insightful discovery, and will eventually become an unstoppable driver for the transformation of economy and business opportunities.
This special issue aims to highlightIAIconcept, research scopes and recently technical advancements in industrial data analytics, and make theIAIconcept more visible inAIcommunity. Original contributions, including industrial data driven machine learning techniques, advanced fuzzy logic systems, online optimization algorithms, real-world case studies on industrial applications, and comprehensive surveys with directions, are cordially welcome. Through this special issue, some fundamental concepts and associatedAItechniques forIAIwill be further focused and promoted.
About the issue
The topics of this special issue include, but are not limited to:
Identification of input-output causality from noisy big industrial data
Computational intelligence and machine learning techniques for soft-sensors and predictive modelling
Time-series forecasting, and interval estimate for industrial data
Learning-based reasoning techniques for industrial applications
AI-driven operational optimization and decision-making
AI-based methods for process monitoring, abnormality detection and fault analysis
AI-based planning and scheduling for process industries
Case studies of AI technology for problem solving in process industries, chemical engineering, power systems, industrial robotics, maritime engineering, transportation engineering, civil engineering, and intelligent software engineering