Prediction of Rainfall Using Unsupervised Model based Approach Using K-Means Algorithm
Автор: G.Vamsi Krishna
Статья в выпуске: 1, 2015 года.
Prediction of rainfall has gained a significant importance because of many associated factors like cultivating, aqua-culture and other indirect parameters allied with the rainfall like global heat. Therefore it is necessary to predict the rainfall from the satellite images effectively. In this article, a segmentation algorithm is developed based on Gaussian mixture models. The initial parameters are estimated using k-means algorithm. The process is presented by using an 2-fold architecture, where in the first stage database creation is considered and the second stage talks about the prediction. The performance analysis is carried out using metrics like PSNR, IF and MSE. The developed model analyzes the satellite images and predicts the Rainfall efficiently.
Rainfall prediction, Gaussian mixture model, K-Means algorithm, rainfall estimation, PSNR, MSE
Короткий адрес: https://readera.org/15010114
Список литературы Prediction of Rainfall Using Unsupervised Model based Approach Using K-Means Algorithm
- K. Richards and G.D. Sullivan," Estimation of Cloud Cover using Colour and Texture" Intelligent Systems Group, University of Reading, RG6 2AY,2006.
- Malay K. Kundu and Priyank Bagrecha,"Color Image Retrieval Using M-Band Wavelet Transform Based Color-Texture Feature".
- Kuo-Lin Hsu, X. Gao, and Soroosh Sorooshian,"Rainfall Estimation Using Cloud Texture Classification Mapping".
- Liu Jian and Xu Jianmin," An Automated, Dynamic Threshold Cloud Detection Algorithm for FY-2C Images", National Satellite Meteorological Center, Beijing, 100081, China.
- Anuj Srivastava and Ian H. Jermyn, "Looking for Shapes in Two-Dimensional, Cluttered Point Clouds", IEEE Transaction.
- Yanling Hao, Wei ShangGuan,Yi Zhu, and YanHong Tang," Contented-Based Satellite Cloud Image Processing and Information Retrieval".
- Aleksey Golovinskiy, Vladimir G. Kim and Thomas Funkhouser,"Shape-based Recognition of 3D Point Clouds in Urban Environments".
- Peter S. Masika, "Cloud height determination and comparison with observed rainfall by using meteosat second generation (msg) imageries",Kenya Meteorological Department, 2006.
- Shou Yixuan, Li Shenshen, Shou Shaowen and Zhao Zhongming, "Application of a cloud-texture analysis scheme to the cloud cluster structure recognition and rainfall estimation in a mesoscale rainstorm process", Advances in Atmospheric Sciences, Science Press, co-published with Springer-Verlag GmbH, 0256-1530 (Print) 1861-9533 (Online), Volume 23, Number 5 / October, 2006, 767-774.
- Wei Shangguan; Yanling Hao; Zhizhong Lu; Peng Wu, "The Research of Satellite Cloud Image Recognition Base on Variational Method and Texture Feature Analysis", Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on Volume , Issue , 23-25 May 2007.
- Valmik B Nikam and B.B. Meshram, "Modeling Rainfall Prediction using DataMining Method", Fifth International Conference on Computational Intelligence, Modeling and Simulation, Issue No: 2166-8531, PP:132-136, 2013.
- F.Dell Acqua and P.Gamba, "A simple Model Approach to the problem of meteorological object Tracking", Volume: 1, Issue No: 7803-6359, PP: 2152-2154, Italy, 2000.
- Sanjay Chakraborty, Prof.N.K. Nagwani, Lopamudra dey, "Weather Forecasting using Incremental K-means Clustering", International Conference in High Performance Architechture and Grid Computing, Vol.169, Part-2, PP:338-341,2011.
- Marwa F.AI-Roby, Alaa M.El-Halees, Data Mining Techniques for Wind Speed Analysis",Journal of Computer Engineering, ISSN:2010-1619, Vol-2 ,No:1, PP:1-5, 2011.
- Abhay Kumar, Ramnish Sinha, Daya Shankar Verma, Vandhana Bhattacherjee, Satendra Singh (2012), "Modeling using K-Means Clustering Algorithm", First International Conference on Recent Advances in Information Technology, Vol:4, Issue-1, Issue No: 4577-0697, PP:1-5.
- Zohreh Nazeri and Jianping Zhang "Mining Aviation Data to Understand Impacts of Severe Weather on Airspace Syatem Performance", Proceedings of the International Conference on Information Technology: Coding and Computing[ITCC'OL], Volume-1, ISSN: 7695-1506, PP: 1-6, 2002.
- N.RAJASHEKAR and T.V.RAJINIKANTH, "weather analysis of Guntur district of Andhra region hybrid SVM data mining techniques", international journal of engineering and advanced technology (IJEAT), ISSN: 2449-8958, Volume-3, issue-4, PP: 133-136, April 2014.
- ANKITH SINGH, Dr. BHUPESH GOUR, ANSHUL KHANDELWAL and HARSHA LACKHWANI, "an efficient clustering method for atmospheric conditions prediction using art algorithm", international journal of advanced research in computer engineering and technology, volume-1, issue-1, PP: 12-17, march 2012.
- HANS-HENRIK BENZON and THOMAS BOVITH, "simulation and prediction of weather radar clutter using a wave propagator on high resolution NWP data", IEEE transactions an antennas and propagation, volume: 56, No: 12, PP: 3885-3890, December 2008.
- Shaminder Singh and Jasmeen Gill,"Temporal Weather Prediction using Back Propagation based Genetic Algorithm Technique", DOI: 10.5815/ijisa.2014.12.08,PP:55-61.
- Folorunsho Olaiya and Adesesan Barnabas Adeyemo "Application of Data Mining Techniques in Weather Prediction and Climate Change Studies", DOI: 10.5815/ijieeb.2012.01.07,PP:51-59.
- Shaminder Singh" Temporal Weather Prediction using Back Propagation based Genetic Algorithm Technique" .J. Intelligent Systems and Applications, 2014, 12, DOI: 10.5815/ijisa.2014.12.08 PP 55-61.