Introduction to the Special Issue on Machine Learning-Guided Intelligent Modeling with Its Industrial Applications

作     者：Xiong Luo Yongqiang Cheng Zhifang Liao 

作者机构：School of Computer and Communication EngineeringUniversity of Science and Technology BeijingBeijing100083China Faculty of TechnologyUniversity of SunderlandSunderlandSR60DDUK School of Computer Science and EngineeringCentral South UniversityChangsha410083China 

出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)

年 卷 期：2024年第141卷第10期

页      面：7-11页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by the Beijing Natural Science Foundation under Grants L211020 and M21032 in part by the National Natural Science Foundation of China under Grants U1836106,62271045,and U2133218 

主　　题：Intelligence bringing intelligent 

摘      要：With the advancement of Artificial Intelligence(AI)technology,traditional industrial systems are undergoing an intelligent transformation,bringing together advanced computing,communication and control technologies,Machine Learning(ML)-based intelligentmodelling has become a newparadigm for solving problems in the industrial domain[1–3].With numerous applications and diverse data types in the industrial domain,algorithmic and data-driven ML techniques can intelligently learn potential correlations between complex data and make efficient decisions while reducing human ***,in real-world application scenarios,existing algorithms may have a variety of limitations,such as small data volumes,small detection targets,low efficiency,and algorithmic gaps in specific application domains[4].Therefore,many new algorithms and strategies have been proposed to address the challenges in industrial applications[5–8].