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A Semi- Supervised Technique for Weather Condition Prediction using DBSCAN and KNN
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 95 - Number 10 |
| Year of Publication: 2014 |
| Authors: Aastha Sharma, Setu Chaturvedi, Bhupesh Gour |
10.5120/16631-6500
|
Aastha Sharma, Setu Chaturvedi, Bhupesh Gour . A Semi- Supervised Technique for Weather Condition Prediction using DBSCAN and KNN. International Journal of Computer Applications. 95, 10 ( June 2014), 21-26. DOI=10.5120/16631-6500
Abstract
Weather condition prediction has always been a keen area of interest among researchers and climate change prediction experts. Due to gradual changes in the atmospheric and climatic conditions the appropriate prediction task has become a formidable challenge. In this paper we propose a semi- supervised weather prediction technique to validate the predictions done for certain atmospheric parameters taken for four years on a day wise basis in a certain city. The experimental outcomes of this work show that this semi supervised technique provides appropriate results and can be used for weather condition prediction & analysis.
References
- A. B Adeymo, "Soft Computing techniques for weather and Climate change studies ",African journal Of Computing , Vol 6, No. 2, June 2013.
- Folorunsho Olaiya, Adesesan Barnabas Adeyemo "Application of Data Mining Techniques in Weather Prediction and Climate Change Studies" I. J. Information Engineering and Electronic Business, 2012, 1, 51-59
- Folorunsho Olaiya , Adesesan Barnabas Adeyemo , "Application of Data Mining Techniques in Weather Prediction and Climate Change Studies", I. J. Information Engineering and Electronic Business,February 2012.
- Casas D. M, Gonzalez A. T, Rodrgíue J. E. A. , Pet J. V. , 2009, "Using Data-Mining for Short-Term Rainfall Forecasting", Notes in Computer Science, Vol. 5518, 487-490
- X. Zhu and A. B. Goldberg" Introduction to Semi-Supervised Learn- ing. Synthesis Lectures on Arti?cial Intelligence and Machine Learning'Morgan & Claypool Publishers, 2009.
- R. Sathya, Annamma Abraham "Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification"(IJARAI) International Journal of Advanced Research in Artificial Intelligence, Vol. 2, No. 2, 2013
- V. Jothi Prakash1, Dr. L. M. Nithya2," A Survey On Semi-Supervised Learning Techniques ", IJCTT ,Vol 8 No. 1, Feb 2014.
- M. Ester, H. P. Kriegel, J. Sander, and X. Xu, "A Density Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise," Proc. Sencond Int'l Conf . Knowledge Discovery and Data Mining(KDD), 1996, pp. 226-231.
- Zahoor Jan, M. Abrar, Shariq Bashir, and Anwar M. Mirza" Seasonal to Inter-annual Climate Prediction Using Data Mining KNN Technique" © Springer-Verlag Berlin Heidelberg 2008.
- V. Jothi Prakash, Dr. L. M. Nithya"A Survey On Semi-Supervised Learning Techniques" International Journal of Computer Trends and Technology (IJCTT) – Vol. 8 number 1– Feb 2014.
- Yujie Zheng, "Clustering Methods in Data Mining with its Applications in High Education ", (ICETC2012)IPCSIT vol. 43 (2012) © (2012) IACSIT Press, Singapore
- Thair Nu Phyu "Survey of Classification Techniques in Data Mining" Proceedings of the International MultiConference of Engineers and Computer Scientists 2009 Vol. IIMECS 2009, March 18 - 20, 2009, Hong Kong
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