Mody University International Journal of Computing and Engineering Research

Open Access Open Access  Restricted Access Subscription Access

An Efficient Approach for Rainfall Forecasting Using Data Mining


Affiliations
1 School of Computing Science and Engineering, Galgotias University, Gautam Buddh Nagar, Uttar Pradesh, India
 

   Subscribe/Renew Journal


Farming as the major occupation of India requires a scientific and analytic focus for its productivity. Agricul-ture and allied sectors like forestry and fisheries accounted for 15-19% of the GDP (Gross Domestic Product) [1]. India is a country having various seasons and different geographical conditions. India’s climate can be classified as a hot tropical country, except the northern states of Himachal Pradesh and Jammu and Kashmir in north and Sikkim in the north eastern hills, which have a cooler, more continental influenced climate. These variations in climate make prediction of weather difficult. Techniques like Machine Learning algorithms are required for studying and predicting the weather conditions. This paper represents an analysis and prediction of rainfall by studying the previous data accumulated in 100 of years [2]. This paper uses basic techniques of Data Mining to conduct a trend analysis on Rainfall Data. We have analyzed data of various regions, implemented suitable data mining techniques based on literature survey to achieve our goal of analyzing and predicting the Rainfall. Hierarchical clustering is used for grouping and clustering similar data together. Regression technique is used to predict the range of values, Graph Extrapolation technique is used to estimate value and to predict the future pattern.

Keywords

Analytics, Clustering, Extrapolation, Prediction.
User
Subscription Login to verify subscription
Notifications
Font Size

  • https://en.wikipedia.org/wiki/Economy_of_India

  • T. V. R. Kanth, V. V. S. S. S. Balaram, and N. Rajasekhar, “Analysis of Indian weather data sets using data mining techniques,” Computer Science & Information Technology, pp. 89-94, 2014.

  • H. D. Shannon, and R. P. Motha, “Managing weather and climate risks to agriculture in North America, Central America and the Caribbean,” Weather and Climate Extremes, vol. 10, part A, pp. 50-56, December 2015.

  • S. Neenu, A. K. Biswas, and A. S. Rao, “Impact of climatic factors on crop production - A review,” Agricultural Reviews, vol. 34, no. 2, pp. 97-106, 2013.

  • https://en.wikipedia.org/wiki/Climate_of_India

  • J. H. Friedman, “Data mining and statistics: What’s the connection?,” in Proceedings of the 29th Symposium on the Interface Between Computer Science and Statistics, 1997.

  • M. Milman, Extrapolation and Optimal Decompositions with Applications to Analysis, 1994.

  • https://data.gov.in/catalog/all-india-area-weighted-monthly-seasonal-and-annual-rainfall-mm

  • S. Paul, S. Ghosh, R. Oglesby, A. Pathak, A. Chandrasekharan, and R. Ramsankaran, “Weakening of Indian summer monsoon rainfall due to changes in land use land cover,” Scientific Reports, vol. 6, article no. 32177, 2016.

  • S. Srivastava, and R. Srivastava, “Adoption of Green Information Technology (GIT) in India - A current scenerio,” Journal of Information and Operations Management, vol. 3, no. 1, pp. 61-63, 2012.


Abstract Views: 306

PDF Views: 137




  • An Efficient Approach for Rainfall Forecasting Using Data Mining

Abstract Views: 306  |  PDF Views: 137

Authors

Satyajee Srivastava
School of Computing Science and Engineering, Galgotias University, Gautam Buddh Nagar, Uttar Pradesh, India
Vivek Kumar
School of Computing Science and Engineering, Galgotias University, Gautam Buddh Nagar, Uttar Pradesh, India

Abstract


Farming as the major occupation of India requires a scientific and analytic focus for its productivity. Agricul-ture and allied sectors like forestry and fisheries accounted for 15-19% of the GDP (Gross Domestic Product) [1]. India is a country having various seasons and different geographical conditions. India’s climate can be classified as a hot tropical country, except the northern states of Himachal Pradesh and Jammu and Kashmir in north and Sikkim in the north eastern hills, which have a cooler, more continental influenced climate. These variations in climate make prediction of weather difficult. Techniques like Machine Learning algorithms are required for studying and predicting the weather conditions. This paper represents an analysis and prediction of rainfall by studying the previous data accumulated in 100 of years [2]. This paper uses basic techniques of Data Mining to conduct a trend analysis on Rainfall Data. We have analyzed data of various regions, implemented suitable data mining techniques based on literature survey to achieve our goal of analyzing and predicting the Rainfall. Hierarchical clustering is used for grouping and clustering similar data together. Regression technique is used to predict the range of values, Graph Extrapolation technique is used to estimate value and to predict the future pattern.

Keywords


Analytics, Clustering, Extrapolation, Prediction.

References