A fuzzy CBR technique for generating product ideas
| Autor: | Ying-Fu Lo, Shang Hwa Hsu, Muh-Cherng Wu |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
business.industry
Computer science General Engineering computer.software_genre Fuzzy logic Computer Science Applications Artificial Intelligence Product (mathematics) New product development Fuzzy set operations Case-based reasoning Data mining business Baseline (configuration management) computer Fuzzy ahp |
| Zdroj: | Expert Systems with Applications. 34:530-540 |
| ISSN: | 0957-4174 |
| Popis: | This paper presents a fuzzy CBR (case-based reasoning) technique for generating new product ideas from a product database for enhancing the functions of a given product (called the baseline product). In the database, a product is modeled by a 100-attribute vector, 87 of which are used to model the use-scenario and 13 are used to describe the manufacturing/recycling features. Based on the use-scenario attributes and their relative weights - determined by a fuzzy AHP technique, a fuzzy CBR retrieving mechanism is developed to retrieve product-ideas that tend to enhance the functions of the baseline product. Based on the manufacturing/recycling features, a fuzzy CBR mechanism is developed to screen the retrieved product ideas in order to obtain a higher ratio of valuable product ideas. Experiments indicate that the retrieving-and-filtering mechanism outperforms the prior retrieving-only mechanism in terms of generating a higher ratio of valuable product ideas. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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