IMPLEMENTING DATA SCIENCE FOR RAINFALL PREDICTION WITH VARIABLE PARAMETERS THROUGH MACHINE LEARNING AND ADVANCED BIG DATA TOOLS.

Article Sidebar

PDF Untitled
Published: Feb 20, 2018
DOI: https://doi.org/10.26483/ijarcs.v9i1.5344
Keywords:
Weather parameters, Rainfall, Data Science, Machine Learning, Clustering.

Main Article Content

Rahamathulla Vempalli
Rayalaseema University, Kurnool
S. Ramakrishna

Abstract

India is an agriculture based country. Most of the population is living in villages and their occupation is agriculture. As Mahathma Gandhiji said “The Development of the nation is depends on the development of the villagesâ€. Rainfall is most required factor for agriculture. The complete agriculture depends on Rainfall [2]. Due to abnormal conditions of the weather the formers are forgoing their crops and indulging as debtors. Most of the farming areas in the country are depends on the Rainfall, In India only 34% of the fertile land getting water through the rivers . So there is a huge necessity for Prediction of Rainfall. The Rainfall is one the most important Phenomena of the weather. The weather may be described as change-in-climate. Rapid changes occurred in the weather. It is the major task to understand and predict the weather.
The weather parameters are
• Temperature
• Humidity
• Wind speed
• Wind direction
• Rainfall
• Pressure

The major occupation of the Indian people is Agriculture. Rainfall plays a major role in agriculture. The prediction of rainfall helps the farmer to decide the type of a crop. The crops broadly categorized in to 2 types.
1) Short Term crops
2) Long Term crops
Short Term Crops: The short term crops required less water and the crop completes with in the short period. Eg: Leafs,
Long Term Crops: The long term crops required more water and the crop takes long period such as 3 months, 6 months, 1 year etc.
Most of the crops are depends on Rainfall. So the prediction of rainfall helps the farmers to decide the type of crop.

Downloads

Download data is not yet available.

Article Details

Issue
Vol. 9 No. 1 (2018): January-February 2018
Section
Articles

COPYRIGHT

Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.

Authors who publish with this journal agree to the following terms:

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
  • The journal allows the author(s) to retain publishing rights without restrictions.
  • The journal allows the author(s) to hold the copyright without restrictions.
Author Biography

Rahamathulla Vempalli, Rayalaseema University, Kurnool

MCA DEPARTMENT, ASSISTANT PROFESSOR

References

Gandhi, Mahatma “Gandhi, An Auto Biography†Beacon Press, December 1983.

Shaminder singh, Baljeet singh “Training Back Propagation Neural Networks with genetic algorithm for weather forecasting†IEEE 8th International Symposium on intelligent systems and informatics sebia, 2010.

Saeed Reza Khodashenas et al, Najmeh Khalili “Daily Rainfall Forecasting for Mashhad Synoptic Station using Artificial Neural networks, International Conference on Environmental and Computer Science IPCBEE , 2011. VOL.19 (2011).

Zaman M. Faisal, H.Hirose, Sumi S. Monira “ Comparision of Artificially Intelligent Methods in Short Term Rainfall Forecast†the 13th International Conference on Computer And Information Technology, Vol. PID728, 2010.

Foster provost, Tom Fawcett,†Data Science for Business†‘O Relly Media, 2016.

Rachel Schutt, “Doing Data Science†Orelly Meida, 2013.

Peter A Flach “Machine Learningâ€, springer Publications-2018.

Pranjal Awasthi, Maria Florina Balcan, Konstain Voevodski “ Local algorithms for interactive clustering†volume 18 Feb-2017, Journal of Machine Learning Research

Gowthami, “The Prediction of Indian Monsoon Rainfall-A Regression Approachâ€, Solstice-An Electronic Journal of Geography and mathematics.

Dr. Vincent Granville, “Developing Analytic Talent†Wiley, April 2014.