Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values
Data Mining and Knowledge Discovery
Expert Systems with Applications: An International Journal
A rough set-based case-based reasoner for text categorization
International Journal of Approximate Reasoning
Expert Systems with Applications: An International Journal
ICICA'11 Proceedings of the Second international conference on Information Computing and Applications
Application of decision-making techniques in supplier selection: A systematic review of literature
Expert Systems with Applications: An International Journal
Integration of semi-fuzzy SVDD and CC-Rule method for supplier selection
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
Petroleum is an important strategic material which is connected with the vitals and safety of the national economy, and the supplier selections are related to the safety of petroleum production and supply. However, the traditional approaches for supplier selections are limited in subjective evaluation of weights, inaccurate assessing rules, and inefficient decision-making. Although most of the current methods are widely applied in corporation management, a more efficient approach needs to be proposed for supplier selection of oil enterprise. This paper summarizes the particular characteristics of the supply chain of Chinese petroleum enterprises, analyzes the limitations of the traditional methods of supplier selection, and brought forward the method based on case reasoning system (CBR) for petroleum enterprises. The method based on data mining techniques which solves three key problems of CBR, includes calculating the weights of the attributes with information entropy in case warehouse organizing process objectively, evaluating the similarities with k-prototype clustering between the original and target cases in case retrieving process exactly, and extracting the potential rules with back propagation neural networks from conclusions in maintenance and revising process efficiently. It demonstrates the advantages, practicability and validity of this method via case study finally.