Combining numerical and linguistic information in group decision making
Information Sciences: an International Journal
An integrated multicriteria decision-making methodology for outsourcing management
Computers and Operations Research
A fuzzy CBR technique for generating product ideas
Expert Systems with Applications: An International Journal
A method for group decision making with multi-granularity linguistic assessment information
Information Sciences: an International Journal
An association-based case reduction technique for case-based reasoning
Information Sciences: an International Journal
A hierarchical design of case-based reasoning in the balanced scorecard application
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Loss and gain functions for CBR retrieval
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A method based on stochastic dominance degrees for stochastic multiple criteria decision making
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
A fully personalization strategy of E-learning scenarios
Computers in Human Behavior
Expert Systems with Applications: An International Journal
Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction
Computers and Operations Research
Probability: Theory and Examples
Probability: Theory and Examples
An integrated case-based reasoning and MCDM system for Web based tourism destination planning
Expert Systems with Applications: An International Journal
Case-based parametric design system for test turntable
Expert Systems with Applications: An International Journal
A fuzzy case based reasoning approach to value engineering
Expert Systems with Applications: An International Journal
Learning fuzzy rules for similarity assessment in case-based reasoning
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Case retrieval is a primary step in case-based reasoning (CBR). It is important to measure the similarity between each historical case and the target case during the case retrieval process. In recent years, some methods for similarity measure with multiple formats of attribute values can be found in the practical CBR applications, but the in-depth study is still lacking. The objective of this paper is to develop a new method for hybrid similarity measure with five formats of attribute values: crisp symbols, crisp numbers, interval numbers, fuzzy linguistic variables and random variables. First, for each format of the attribute values, the calculation formula to measure the attribute similarity is presented. Then, the method for measuring hybrid similarity between each historical case and the target case is given by aggregating attribute similarities using the simple additive weighting method, and the proper historical case(s) can be retrieved according to the obtained hybrid similarities afterwards. Finally, a case study in the field of emergency response towards gas explosion is introduced to illustrate the use of the proposed method.