Rainfall Prediction using Bpnn
M Krishna1, S Mohanbabu Chowdary2, Bandlamudi S B P Rani3, Sanjeevi P4
1M Krishna, Department of Computer Science Engineering, Sir C R Reddy College of Engineering, Eluru, Andhra Pradesh, India.
2S Mohanbabu Chowdary, Department of Computer Science Engineering, Sir C R Reddy College of Engineering, Eluru, Andhra Pradesh, India.
3Bandlamudi S B P Rani, Department of Computer Science Engineering, Sir C R Reddy College of Engineering, Eluru, Andhra Pradesh, India.
4Sanjeevi P, Department of Computer Science Engineering, Sir C R Reddy College of Engineering, Eluru, Andhra Pradesh, India.
Manuscript received on 08 April 2019 | Revised Manuscript received on 15 April 2019 | Manuscript Published on 26 July 2019 | PP: 661-668 | Volume-8 Issue-6S4 April 2019 | Retrieval Number: F11350486S419/19©BEIESP | DOI: 10.35940/ijitee.F1135.0486S419
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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: Gauge of precipitation and ground water of an express area will assist water aid executives to preference the application of water and limit of water. The records for envisioning organized in time direction of movement i.e., functions that helpers for parent are yr, month, common precipitation, ground water level. For this conjecture lower back expanded neural frameworks with widely appealing weight replace at n-degree disguised layer changed into made to constrain the bungle fee and enhance the preference. Our system engaged with information estimate and statistics discernment challenge to mining process. for purchasing ANN based figure with APRIORI-NN based totally portrayal method become taken into consideration to widen and assist water aid chiefs.
Keywords: Rainfall, Prediction, NARX Neural Network, Feed Forward, Back Propagation.
Scope of the Article: Computer Science and Its Applications