TY - GEN
T1 - The Performance of Weather Forecasting using Data Mining and Evolutionary Algorithms
T2 - 12th INDIACom; 5th International Conference on Computing for Sustainable Global Development, INDIACom 2018
AU - Veera Ankalu, V.
AU - Apparao, G.
AU - Srinivasa Murthy, Y. V.
N1 - Publisher Copyright:
Copy Right © INDIACom-2018.
PY - 2018
Y1 - 2018
N2 - Weather plays an important role in day-to-day life. The process of predicting weather is an emerging issue to be solved and need historical quantitative data for proper analysis. The present state of atmospheric conditions will help to analyze how weather evolves from state to state. Weather prediction is basically based upon the historical time series data. The basic Data mining operations and Numerical methods are employed to get a useful pattern from a huge volume of data set. Different testing and training scenarios are performed to obtain the accurate result. To perform these kinds of predictions we are identifying the datasets. Collection of the data sets of a particular region weather report from 1901 to 2001 with 11 attributes. The collected datasets undergo pre-processing. Then clustering operation, Curve fitting and Extrapolation methods are applied, proceeding with back propagation. The Back propagation and Extrapolation results are compared. The Best future results are predicted.
AB - Weather plays an important role in day-to-day life. The process of predicting weather is an emerging issue to be solved and need historical quantitative data for proper analysis. The present state of atmospheric conditions will help to analyze how weather evolves from state to state. Weather prediction is basically based upon the historical time series data. The basic Data mining operations and Numerical methods are employed to get a useful pattern from a huge volume of data set. Different testing and training scenarios are performed to obtain the accurate result. To perform these kinds of predictions we are identifying the datasets. Collection of the data sets of a particular region weather report from 1901 to 2001 with 11 attributes. The collected datasets undergo pre-processing. Then clustering operation, Curve fitting and Extrapolation methods are applied, proceeding with back propagation. The Back propagation and Extrapolation results are compared. The Best future results are predicted.
UR - https://www.scopus.com/pages/publications/105010384017
UR - https://www.scopus.com/inward/citedby.url?scp=105010384017&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:105010384017
T3 - 12th INDIACom; 5th International Conference on "Computing for Sustainable Global Development", INDIACom 2018
SP - 4935
EP - 4939
BT - 12th INDIACom; 5th International Conference on "Computing for Sustainable Global Development", INDIACom 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 March 2018 through 16 March 2018
ER -
