Soft Computing tools are becoming very popular in solving hydrological problems. These tools have immense strength to deal with such complex problems. Water Table elevation estimation is an important aspect to understand the mechanism of ground water resources. The present study aims at the application of Artificial Neural Networks (ANN) & Fuzzy logic for simulation of water table elevation. This paper also investigates the best model to forecast water table elevation. Ten ANN models are developed in this study. These developed models are trained, tested and validated on the available data of Budaun District. Comparing observed data and the estimated data through developed ANN models and Fuzzy models, it has been observed that the developed Fuzzy models predict better results for four models and for model-5 ANN bore better results.
목차
Abstract 1. Introduction 2. Groundwater Resource 3. Artificial Neural Network 4. Fuzzy Methodology 5. Study Area 6. Methodology 7. Development of Models 7.1 Development of Basic Models 7.2 ANN Water table Elevation Fluctuation Models 7.3 Development of Fuzzy Models 8. Results and Discussion 8.1 Comparative Analysis of ANN Models and Fuzzy Models for Water Table Elevation Fluctuation. 9. Summary and Conclusions Acknowledgments References
보안공학연구지원센터(IJAST) [Science & Engineering Research Support Center, Republic of Korea(IJAST)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Advanced Science and Technology
간기
월간
pISSN
2005-4238
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Advanced Science and Technology Vol.51