A Case-Based Reasoning Approach to Formulating University Timetables Using Genetic Algorithms

2005 ◽  
pp. 76-83 ◽  
Author(s):  
Alicia Grech ◽  
Julie Main
Keyword(s):  
Genetic Algorithms ◽  
Case Based Reasoning ◽  
Case Based

Retrieving Assembly Part Design Using Case-Based Reasoning and Genetic Algorithms

2005 ◽  
Author(s):  
Guanghsu A. Chang ◽  
Cheng-Chung Su ◽  
John W. Priest
Keyword(s):  
Artificial Intelligence ◽  
Genetic Algorithms ◽  
Nearest Neighbor ◽  
Similarity Measures ◽  
Experimental Results ◽  
Case Based Reasoning ◽  
Feature Weight ◽  
Similar Part ◽  
Case Base ◽  
Case Based

Artificial intelligence (AI) approaches have been successfully applied to many fields. Among the numerous AI approaches, Case-Based Reasoning (CBR) is an approach that mainly focuses on the reuse of knowledge and experience. However, little work is done on applications of CBR to improve assembly part design. Similarity measures and the weight of different features are crucial in determining the accuracy of retrieving cases from the case base. To develop the weight of part features and retrieve a similar part design, the research proposes using Genetic Algorithms (GAs) to learn the optimum feature weight and employing nearest-neighbor technique to measure the similarity of assembly part design. Early experimental results indicate that the similar part design is effectively retrieved by these similarity measures.

Computer aided diagnosis with case-based reasoning and genetic algorithms

2002 ◽  
Vol 15 (1-2) ◽  
pp. 45-52 ◽  
Author(s):  
Elisabet Golobardes ◽  
Xavier Llorà ◽  
Maria Salamó ◽  
Joan Martı́
Keyword(s):  
Genetic Algorithms ◽  
Computer Aided Diagnosis ◽  
Case Based Reasoning ◽  
Computer Aided ◽  
Aided Diagnosis ◽  
Case Based

Case-Based Reasoning Model with Genetic Algorithms, Group Decision-Making and Template Reduction

2016 ◽  
Vol 25 (02) ◽  
pp. 1550032 ◽  
Author(s):  
Aijun Yan ◽  
Hairuo Song ◽  
Pu Wang
Keyword(s):  
Decision Making ◽  
Genetic Algorithms ◽  
Group Decision Making ◽  
Nearest Neighbor ◽  
Group Decision ◽  
Small Samples ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Attribute Weights ◽  
Case Based

Case retrieval, case reuse and case retention are critical to the reasoning performance of the traditional case-based reasoning (CBR) model. In this paper, the integrated use of template reduction technology (TR), genetic algorithms (GA), nearest neighbor (NN) rules and group decision-making (GDM) establishes the CBR-GDM model. First, the TR method of the case base is introduced. Then, an attribute weights optimization using GA is discussed in the case retrieval phase. After that, a case reuse method is carried out with NN and GDM. Finally, 10 data sets from UCI are used to carry out a comparison experiment by 5-fold cross-validation. The classification accuracy rate and the classification efficiency are analyzed under the small samples, before and after the data reduction. The results show that, combined with TR, GA and GDM, the pattern classification performance by CBR can be improved.

Extraction and reuse of design patterns from genetic algorithms using case-based reasoning

2003 ◽  
Vol 9 (1) ◽  
pp. 44-53 ◽  
Author(s):  
E. I. P�rez ◽  
C. A. C. Coello ◽  
A. H. Aguirre
Keyword(s):  
Genetic Algorithms ◽  
Design Patterns ◽  
Case Based Reasoning ◽  
Case Based
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