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Integration of Bacteria Foraging Optimization and Case Base Reasoning for Ground Water Possibility Detection

Chandni Kapoor, Harpreet Bajaj, Navdeep Kaur Published in

International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
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  1. Chandni Kapoor, Harpreet Bajaj and Navdeep Kaur. Article: Integration of Bacteria Foraging Optimization and Case Base Reasoning for Ground Water Possibility Detection. International Journal of Applied Information Systems 2(4):30-35, May 2012. BibTeX

    	author = "Chandni Kapoor and Harpreet Bajaj and Navdeep Kaur",
    	title = "Article: Integration of Bacteria Foraging Optimization and Case Base Reasoning for Ground Water Possibility Detection",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 2,
    	number = 4,
    	pages = "30-35",
    	month = "May",
    	note = "Published by Foundation of Computer Science, New York, USA"


Bacterial Foraging Optimization (BFO) is a population-based numerical optimization algorithm. This technique is proposed by K. M. Passino in 2002 to handle complex problems of the real world. Case-based reasoning is a unique platform of concepts and techniques that touch upon some of the basic issues concerning to knowledge representation, reasoning and learning from experience. In this work, we have integrated Bacteria Foraging Optimization with Case Based Reasoning to detect ground water possibility in a given area. An algorithm has been proposed in this work. A problem case whose ground water possibility is to be determined is input to the system, BFO retrieves the best matching case from the Case Base and the ground water possibility of that Case is proposed as a solution to the problem case


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Bacterial Foraging Optimization, Chemotactic, Case Base Reasoning, Case Retrieval, Ground Water Possibility.