Earticle

초록

영어

In this paper river stage discharge models using Adaptive Neuro- Fuzzy Inference System (ANFIS) and Linear Multiple Regression (MLR) methods have been developed. This paper also investigates the best model to forecast river discharge. From the literature it is clear that ANN models and Fuzzy logic models are quite applicable on river stage discharge modelling. Hence this present study carried out for hybrid ANFIS models. Ten ANFIS models were developed out of which best five ANFIS models are selected. The developed models were trained, tested & validated on the data of Godavari river at Rajahmundry, Dhawalaishwaram Barrage site in Andhra Pradesh. Comparing observed data and the estimated data through developed ANFIS models, it has been proved that the developed ANFIS models predicted better results the traditional models, like MLR.

목차

Abstract
 1. Introduction
 2. Adaptive - Neuro Fuzzy Inference System (ANFIS)
 3. Study Area
 4. Methodology
 5. Performance evaluation criteria
  5.1. Mean Absolute Deviation (MAD)
  5.2. Root Mean Square Error (RMSE)
  5.3. Correlation Coefficient (R)
  5.4. Coefficient of Efficiency (R2)
 6. Models using ANFIS
 7. Models using Multiple Linear Regression
 8. Comparison of Results of Five Developed Best Stage-Discharge ANFIS Models with MLR Models
 9. Conclusions
 References

키워드

저자

• Dinesh C. S. Bisht [ Department of Applied Sciences and Humanities ITM, University, Gurgaon, India ]
• Ashok Jangid [ Department of Applied Sciences and Humanities ITM, University, Gurgaon, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Science and Technology

• 간기

  월간

• pISSN

  2005-4238

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605