Weather Forecasting by using Modified K-Means Intra and Inter Clustering Algorithm
Veera Ankalu Vuyyuru1, G. Appa Rao2
1Veera Ankalu Vuyyuru, Research Scholar, Department of CSE, Gitam University, (Andhra Pradesh), India.
2Dr. G. Appa Rao, Professor, Department of CSE, Gitam University, (Andhra Pradesh), India.
Manuscript received on 19 July 2019 | Revised Manuscript received on 03 August 2019 | Manuscript Published on 10 August 2019 | PP: 517-521 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B10920782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1092.0782S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Urban air pollution causes biggest to the human being. Monitoring and controlling of air pollution becomes an essential thing. Deals with large dataset when forecasting the weather. Hadoop is popular for storing and processing. K-means clustering finds resemblance in small dataset. In proposed system k-means hadoop mapreduce (KM-HMR) deals with implementation of mapreduce with standard k-means clustering. And KM-I2C k-means inter cluster, it maximizes the distance between the cluster and intra cluster minimizes the distance between the clusters. This approaches increases the quality of cluster it becomes efficient and effective.
Keywords: Hadoop, Mapreduce, Clusters, Forecast.
Scope of the Article: Clustering