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Application of Artificial Neural Network and Adaptive Neural-based Fuzzy Inference System Techniques in Estimating of Virtual Water
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 76 - Number 6 |
| Year of Publication: 2013 |
| Authors: Khaled Ahmadaali, Abdol Majid Liaghat, Nader Heydari, Omid Bozorg Haddad |
10.5120/13250-0715
|
Khaled Ahmadaali, Abdol Majid Liaghat, Nader Heydari, Omid Bozorg Haddad . Application of Artificial Neural Network and Adaptive Neural-based Fuzzy Inference System Techniques in Estimating of Virtual Water. International Journal of Computer Applications. 76, 6 ( August 2013), 12-19. DOI=10.5120/13250-0715
Abstract
Wheat, barley, sugerbeet, potato, alfalfa, and corn are common crops produced in Iran, which need the most virtual water volume compared to other crops. Determination of the virtual water for these crops would assist in better management of water resources. The main objective of this study is to find out the best technique for estimating and mapping of virtual water. In this research, the virtual water volume was determined by crop water requirement and crop yields using three ANN structures as well as ANFIS technique. Based on RMSE and R2 the comparison of obtained results predicted through the applied ANNs structures indicate that the RBF outperforms the other models for estimating virtual water for wheat, potato, corn, and barley. Moreover, a comparison between RBF and ANFIS revealed that ANFIS is a promising model, which can be efficient mathematical tool for estimation of crop's virtual water.
References
- Aali, K. A. , Parsinejad, M. , and Rahmani, B. 2009. Estimation of saturation percentage of soil using multiple regression, ANN, and ANFIS techniques. Computer and Information Science 2, P127.
- Alizadeh, A. , and Keshavarz, A. 2005. Status of agricultural water use in Iran. In "Water Conservation, Reuse, and Recycling: Proceedings of an Iranian-American Workshop", pp. 94-105. National Academies Press.
- Allen, R. G. , Pereira, L. , Raes, D. , and Smith, M. 1998a. FAO Irrigation and drainage paper No. 56. Rome: Food and Agriculture Organization of the United Nations, 26-40.
- Allen, R. G. , Pereira, L. S. , Raes, D. , and Smith, M. 1998b. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome 300, 6541.
- Araghinejad, S. , and Burn, D. H. 2005. Probabilistic forecasting of hydrological events using geostatistical analysis/Prévision probabiliste d'événements hydrologiques par analyse géostatistique. Hydrological sciences journal 50.
- Bouwer, H. 2000. Integrated water management: emerging issues and challenges. Agricultural water management 45, 217-228.
- Brown, S. C. , Mason, C. A. , Lombard, J. L. , Martinez, F. , Plater-Zyberk, E. , Spokane, A. R. , Newman, F. L. , Pantin, H. , and Szapocznik, J. 2009. The relationship of built environment to perceived social support and psychological distress in Hispanic elders: The role of "eyes on the street". The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 64, 234-246.
- Dietzenbacher, E. , and Velázquez, E. 2007. Analysing Andalusian virtual water trade in an input–output framework. Regional Studies 41, 185-196.
- Drake, J. T. 2000. "Communications phase synchronization using the adaptive network fuzzy inference system (anfis)," New Mexico State University.
- Fang, S. , Pei, H. , Liu, Z. , Beven, K. , and Wei, Z. 2010. Water resources assessment and regional virtual water potential in the Turpan Basin, China. Water resources management 24, 3321-3332.
- Jang, J. -S. R. , Sun, C. -T. , and Mizutani, E. 1997. Neuro-fuzzy and soft computing-a computational approach to learning and machine intelligence [Book Review]. Automatic Control, IEEE Transactions on 42, 1482-1484.
- Kisi, O. 2007. Evapotranspiration modelling from climatic data using a neural computing technique. Hydrological Processes 21, 1925-1934.
- Laslett, G. , McBratney, A. , Pahl, P. J. , and Hutchinson, M. 1987. Comparison of several spatial prediction methods for soil pH. Journal of Soil Science 38, 325-341.
- Lowry, W. P. 1972. "Compendium of lecture notes in climatology for Class III meteorological personnel," Secretariat of the World Meteorological Organization.
- Montazar, A. , and Zadbagher, E. 2010. An analytical hierarchy model for assessing global water productivity of irrigation networks in Iran. Water resources management 24, 2817-2832.
- Shahlaei, M. , Sabet, R. , Ziari, M. B. , Moeinifard, B. , Fassihi, A. , and Karbakhsh, R. 2010. QSAR study of anthranilic acid sulfonamides as inhibitors of methionine aminopeptidase-2 using LS-SVM and GRNN based on principal components. European journal of medicinal chemistry 45, 4499-4508.
- Wang, Y. -m. , Chang, J. -x. , and Huang, Q. 2010. Simulation with RBF neural network model for reservoir operation rules. Water resources management 24, 2597-2610.
- Zeitoun, M. , Allan, J. , and Mohieldeen, Y. 2010. Virtual water 'flows' of the Nile Basin, 1998–2004: A first approximation and implications for water security. Global Environmental Change 20, 229-242.
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