期刊
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
卷 43, 期 8, 页码 4215-4227出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s13369-017-2838-y
关键词
Rough set; Reduct; Indiscernibility; Genetic algorithm; Prediction; Linear regression
Internet made a drastic change in the way data are collected. There has been huge and huge collections of data. All these data serve no purpose unless some useful information is mined from it. Prediction of future instances will be major research problem. In this work, we adapt a rough and real coded genetic algorithm-based prediction system for prediction of future instances. We adapt rough set in this work because of uncertainties present in the data. Additionally, it is used to eliminate the unwanted attributes. Real coded genetic algorithm is used to predict the values for the unknown instances by making use of multiple linear regression. The model is experimented over agriculture data obtained from Tiruvannamalai district of Tamil Nadu. The experimental results show the viability of proposed research.
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