期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2016
卷号：5
期号：6
页码：11067
DOI：10.15680/IJIRSET.2015.0506181
出版社：S&S Publications
摘要：Lakes are lively system those are insightful to confined climate and to land-use amendment in theneighboring site. Several lakes obtain their water primarily from rainfall, some are conquered by drainage overspill,and several others are illicit by land water systems. As time grows, the areal amount and profundity of water in lakesare indication of effect in climatic factors some of them are rainfall, emission, temperature, and airstream speed.Fluctuations of lake level diverge with the water equilibrium of the lake and their catchment, and might be, in assuredcases, reflect changes in shallow groundwater resources. Prevalent surface fresh water system on the globe. Theseasonal, monthly and yearly surface water level of the lakes alters in retort to an assortment of factors. In this paper wewill use k-medoid clustering and multiple regression technique for lake level forecasting. By use of clustering datamining technique we will classify our data. As lake level changes as per time due to some weather conditions if weefficiently classify historic data. Further we will apply Cubic SVM classifier over the predicted data to computeconsistency of data predicted.
