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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

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Original Research Articles

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2019.8(4): 2054-2061
DOI: https://doi.org/10.20546/ijcmas.2019.804.241


Adaptive Neuro Fuzzy Inference System for Runoff Modelling– A Case Study
Ashish Kumar* and V.K. Tripathi
Department of Farm Engineering, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India
*Corresponding author
Abstract:

Runoff simulation models were developed to predict runoff for basin of West Godavari district, Andhra Pradesh by utilizing adaptive neuro-fuzzy inference system (ANFIS).Combinations of variables like previous three day stage, previous two day stage, previous one day stage, previous three day run off, previous two day run off, previous one day runoff as input and present day runoff as output were explored. The performance of different ANFIS based models during training and testing periods were evaluated through correlation coefficient (r), coefficient of efficiency (CE) and root mean square error (RMSE). Results of different combination of input per membership function (MFs) were compared and it was depicted that ANFIS model with three MFs per input is having reasonable accuracy for triangular membership function with the values of r (0.991), CE (99.1%) and RMSE (529.93 m3/s). ANFIS model with three MFs per input performed best among trapezoidal member function applied with r, CE and RMS E values 0.993, 99.0% and 468.40 m3/s, respectively. ANFIS model with generalized bell membership function and one MF per input was selected as the best performing model with r (0.947), CE (96.8%) and RMSE (1265.56 m3/s). Trapezoidal, 3 is the best simulation model among all ANFIS model.


Keywords: Triangular, Trapezoidal, Generalized bell membership function, ANFIS, watershed, Basin
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How to cite this article:

Ashish Kumar and Tripathi, V.K. 2019. Adaptive Neuro Fuzzy Inference System for Runoff Modelling– A Case Study.Int.J.Curr.Microbiol.App.Sci. 8(4): 2054-2061. doi: https://doi.org/10.20546/ijcmas.2019.804.241