Title :
Collaborative Intelligent Diagnosis on Supply Chain Partnerships Based on the Integration of ES and SVMs
Author :
Li, Hui ; Li, Xiangyang ; Sun, Jie
Author_Institution :
Sch. of Manage., Harbin Inst. of Technol., Heilongjiang
Abstract :
To identify trust states among supply chain partners, expert systems (ES) and support vector machines (SVMs) were integrated to diagnose supply chain partnerships collaboratively. As a result, coordinated supply chain cooperations could be guaranteed. After analyzing the research evolution of inter-firm relationships in supply chain, trust in partnerships, and cooperation actualization process, the concept of supply chain partnerships diagnosis (SC-PD) was proposed. Intelligent collaborative trust diagnosis process, algorithms, and reasoning structure of supply chain partnerships based on hybrid reasoning which was composed of rule-based reasoning (RBR), soft case-based reasoning (SCBR), and SVMs were built up respectively. At last, the hybrid reasoning technique of partnerships diagnosis was applied into the diagnosis on trust of financial-control competence of chain partners
Keywords :
case-based reasoning; diagnostic expert systems; groupware; supply chain management; support vector machines; collaborative intelligent diagnosis; expert systems; intelligent decision support system; rule-based reasoning; soft case-based reasoning; supply chain partnerships; support vector machines; Algorithm design and analysis; Artificial intelligence; Collaboration; Decision support systems; Diagnostic expert systems; Hybrid intelligent systems; Intelligent structures; Neural networks; Supply chains; Support vector machines; ES; SVMs; Supply chain partnerships diagnosis; hybrid reasoning; intelligent decision support system;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1714447