A Fuzzy Entropy Algorithm For Data Extrapolation In Multi-Compressor System

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@InProceedings{Brar:2007:WCE,

• author = "Gursewak S Brar and Yadwinder S Brar and Yaduvir Singh",
• title = "A Fuzzy Entropy Algorithm For Data Extrapolation In Multi-Compressor System",
• booktitle = "Proceedings of the World Congress on Engineering, WCE 2007",
• year = "2007",
• volume = "I",
• pages = "105--110",
• address = "London",
• month = jul # " 2-4",
• keywords = "genetic algorithms, genetic programming, fuzzy entropy, incomplete data, classification, knowledge discovery, multi-compressor system",
• isbn13 = "978-988-98671-5-7",
• URL = "http://www.iaeng.org/publication/WCE2007/WCE2007_pp105-110.pdf",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.2111",
• bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
• contributor = "CiteSeerX",
• language = "en",
• oai = "oai:CiteSeerXPSU:10.1.1.149.2111",
• abstract = "In this paper incomplete quantitative data has been dealt by using the concept of fuzzy entropy. Fuzzy entropy has been used to extrapolate the data pertaining to the compressor current. Certain attributes related to the compressor current have been considered. Test data of compressor current used in this knowledge discovery algorithm knows the entire attribute clearly. The developed algorithm is very effective and can be used in the various application related to knowledge discovery and machine learning. The developed knowledge discovery algorithm using fuzzy entropy has been tested on a multi-compressor system for incomplete compressor current data and it is found that the error level is merely 4.40percent, which is far better than other available knowledge discovery algorithms",

}

Genetic Programming entries for Gursewak S Brar Yadwinder Singh Brar Yaduvir Singh

Citations