Expert systems are used in many industries, occupations and commercial sectors — particularly in the developing world where experts may be thin on the ground. Examples include agriculture, education, environment, law, manufacturing, medicine, power systems, tax assessments and loan applications. Today'...
Expert Systems with Applications ☑️出版社:Elsevier ☑️ISSN:0957-4174 E-ISSN:1873-6793 ☑️影响因子:8.5 ☑️期刊分区:JCR1区,中科院1区(TOP) ☑️检索数据库:SCIE & Scopus 在检 ☑️出刊频率:月刊,最新一期Volume 238, Part E In progress (15 March 2024) ☑️数据库收录...
This book provides a wide coverage of the basic concepts of expert systems together with the applications in the areas of structural, construction, transportation, and environmental engineering. The material and scope are directed primarily to practicing architects, engineers, system designers, programmers...
This chapter discusses an approach and example of expert systems embedded in administrative applications. Originally, BIM was a software house exhibiting an activity in the development of administrative applications for small and medium sized companies using a traditional software development practice. Since...
我院计算机科学与技术专业硕士研究生黄亚鑫为第一作者、指导教师霍峥为通讯作者在中科院1区top期刊《Expert Systems with Applications》上发表了题为《DRA: A Data Reconstruction Attack on Vertical Federated k-means Clustering》的学术...
The trading algorithm based on the volatility fore-casting recruiting investor sentiment could be further applied in electronic trading and other artificialintelligence decision support systems.? 2010 Elsevier Ltd. All rights reserved.1. IntroductionThis study bridges the gap between option trading and ...
我校计算机工程学院教师孙逊在图像特征点检测上的最新研究成果《On the generalized k-cosine arithmetic-mean curvature for multi-scale corner detection》被人工智能领域重要国际期刊Expert Systems With Applications(ESWA被SCI检索,位于JCR分区...
EXPERT SYSTEMS WITH APPLICATIONSEXPERT SYST APPL是一本国际期刊,其重点是交换与全球工业,政府和大学应用的专家和智能系统有关的信息。该期刊的主旨是发表有关专家和智能系统的设计,开发,测试,实施和/或管…
Expert Systems with Applications j our nal homepage: . el sevi er . com/ l ocat e/ eswa The proposed method incorporates both sampling techniques and cost-sensitive learning, which are two common approaches to tackle the problemof imbalanced data. By introducing ‘‘interval variables”, these ...