International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 138 | Views: 204

Review Papers | Computer Science & Engineering | India | Volume 5 Issue 7, July 2016


A Review of Literature on Water Resource Management Using Data Mining Techniques

Pratap Singh Solanki | R. S. Thakur


Abstract: Water, a limited natural resource and most precious elements for all live beings on planet. It is not only essential for human being and plants but also very essential for Agriculture, Environment, Household, Power generation, Industries, Navigation, and Recreation etc. India is an agriculture country and about seventy percent of Indian population depend on the agriculture. Our economy is also based on agriculture. This article aims to review the studies related to use of data mining techniques in the field of water resource sector for Water Management. Presently, the Water Resource Management has become most challenging, interesting and fascinating domain around the word since last many years. Scientist tries to predict the Rainfall, Flood Warning, Water Inflow, Water Availability and Requirements etc. based on huge available metadata using various methods. In this article, we try to search the use of data mining techniques for predicting the inflow, drought possibility, weather report, rainfall, evaporation, temperature, wind speed etc. This paper provides the survey of some literature and work done by the researches using various algorithms and modeling method viz. Associations rules, Classification, Clustering, Decision Tree, and Artificial Neural Network etc. . Data Mining is a collection of techniques for efficient automated discovery of previously unknown, valid, novel, useful and understandable pattern in large databases thus facilitating decision makers to make proactive, knowledge-drive decision.


Keywords: Data Mining, Water Resource Management, Weather forecasting, Rainfall, Inflow


Edition: Volume 5 Issue 7, July 2016,


Pages: 291 - 295


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