Fish disease diagnosis is a complicated process and requires high level of expertise. However, there’s no accepted general knowledge in fish disease diagnosis. This paper describes a CBR (case-based reasoning) system for fish disease diagnosis. A two-step case retrieve model is proposed in this paper.


case-based reasoning fish disease diagnosis nearest neighbor 


  1. Abdus Salam Khan, Achim Hoffmann. Building a case-based diet recommendation system without a knowledge engineer. Artificial Intelligence in Medicine, 2003(27): 155-179Google Scholar
  2. Anil Varma, Nicholas Roddy. ICARUS: design and deployment of a case-based reasoning system for locomotive diagnostics. Engineering Applications of Artificial Intelligence, 1999 (12): 681-690Google Scholar
  3. Daniel Zeldis, Shawn Prescott. Fish disease diagnosis program-problems and some solutions. Aquacultural Engineering, 2000(23): 3-1Google Scholar
  4. Daoliang Li, Zetian Fu, Yanqing Duan. Fish-Expert: a web-based expert system for fish disease diagnosis. Expert Systems with Applications, 2002(23): 311-320Google Scholar
  5. Florian Hartge, Thomas Wetter, Walter E. Haefeli. A similarity measure for case based reasoning modeling with temporal abstraction based on cross-correlation. Computer Methods and Programs in Biomedicine, 2006(8): 41-48Google Scholar
  6. I. Watson. Case-based reasoning is a methodology not a technology. Knowledge-Based Systems, 1999(12): 303-308Google Scholar
  7. Isabelle Bichindaritz, Cindy Marling. Case-based reasoning in the health sciences: What’s next? Artificial Intelligence in Medicine, 2006(36): 127-135Google Scholar
  8. Isabelle Bichindaritz. Memoire: A framework for semantic interoperability of case-based reasoning systems in biology and medicine. Artificial Intelligence in Medicine, 2006(36): 177-192Google Scholar
  9. Kyung-Sup Kim, Ingoo Han. The cluster-indexing method for case-based reasoning using self-organizing maps and learning vector quantization for bond rating cases. Expert Systems with Applications, 2001(21): 147-156Google Scholar
  10. Nirmalie Wiratunga, Susan Craw, Bruce Taylor, Genevieve Davis. Case-based reasoning for matching Smarthouse technology to people’s needs. Knowledge-Based Systems, 2004(17): 139-146Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Wei Zhu
    • 1
  • Daoliang Li
    • 1
  1. 1.College of Information and Electrical EngineeringChina Agricultural UniversityChina

Personalised recommendations