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Fuzzy Logic based Cricket Player Performance Evaluator

Artificial Intelligence Techniques - Novel Approaches & Practical Applications
© 2011 by IJCA Journal
Number 1 - Article 3
Year of Publication: 2011
Gursharan Singh
Nitin Bhatia
Sawtantar Singh

Shripal Vijayvargiya and Pratyoosh Shukla. A Genetic Algorithm with Clustering for Finding Regulatory Motifs in DNA Sequences. IJCA Special Issue on Artificial Intelligence Techniques - Novel Approaches & Practical Applications (1):31–35, 2011. Full text available. BibTeX

	author = {Shripal Vijayvargiya and Pratyoosh Shukla},
	title = {A Genetic Algorithm with Clustering for Finding Regulatory Motifs in DNA Sequences},
	journal = {IJCA Special Issue on Artificial Intelligence Techniques - Novel Approaches & Practical Applications},
	year = {2011},
	number = {1},
	pages = {31--35},
	note = {Full text available}


Cricket is amongst the most popular sports. Performance of players directly affects their ranking internationally. We propose a fuzzy logic based technique to evaluate the performance of cricket players. Various input parameters are being considered which are scaled using linguistic variables and a very simple yet effective software tool is developed to compute the effect of input parameters on the ranking of the players.


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