A novel approach for knowledge extraction from Artificial Neural Networks

References

• Allen, R.G., Pereira, L.S., Raes, D., and Smith, M. (2004). FAO irrigation and drainage paper, No. 56, crop evapotranspiration, (guidelines for computing crop water requirements). 300 p.
   Google Scholar
• Bose, N.K., and Liang, P. (1998). Neural network fundamentals with graphs, algorithms and applications. Tata McGraw-Hill Publication. New York.
   Google Scholar
• Chaudhari, N., Londhe, S.N., and Khare, K. (2012). “Estimation of pan evaporation using soft computing tools.” Int. J. Hydrol. Sci. Technol., 2(4), 373–390.10.1504/IJHST.2012.052375
   Google Scholar
• Dawson, C.W., and Wilby, R.L. (2001). “Hydrological modeling using artificial neural networks.” Prog. Phys. Geogr., 25(1), 80–108.10.1191/030913301674775671
   Web of Science ®Google Scholar
• Fritschen, L.J. (1966). “Energy balance method.” Proc. Am. Soc. Agric. Eng. Conf. on Evapo-transpiration and its role in Water Resources Management, December 5–6, Chicago, IL. St. Joseph, MI, 34–37.
   Google Scholar
• Gallant, S.I. (1988). “Connectionist expert systems.” Commun. ACM, 31(2), 152–169.10.1145/42372.42377
   Web of Science ®Google Scholar
• Guitjens, J.C. (1982). “Models of alfalfa yield and evapotranspiration.” J. Irrig. Drain. Div. Proc. Am. Soc. Civ. Eng., 108(IR3), 212–222.
   Web of Science ®Google Scholar
• Harbeck, G.E. (1962). A practical field technique for measuring reservoir evaporation utilizing mass-transfer theory. Geological Survey Professional Paper 272-E. US Government Printing Office, Washington, D.C, 101–105.
   Google Scholar
• Jain, A., and Kumar, S. (2009). “Dissection of trained neural network hydrologic models for knowledge extraction.” Water Resour. Res., 45(7), W07420.
   Google Scholar
• Kingston, G.B., Maier, H.R., and Lambert, M.F. (2008). “A probabilistic method for assisting knowledge extraction from artificial neural networks used for hydrological prediction.” Mathe. Comput. Model., 44, 499–512.
   Google Scholar
• Kohler, M.A., Nordenson, T.J., and Fox, W.E. (1955). Evaporation from pans and lakes. Weather Bureau Research Paper 38, US Department of Commerce, Washington, D.C..
   Google Scholar
• Londhe, S.N., and Shah, S.S. (2017). Evaluation of pan evaporation model developed using ANN. Development of Water Resources in India, Water Science and Technology Library 75. Springer International Publishing, 221–231.
   Google Scholar
• Maier, H.R., and Dandy, G.C. (2000). “Neural networks for prediction and forecasting of water resources variables: a review of modelling issues and applications.” Elsevier Environ. Model. Softw., 15(2000), 101–124.10.1016/S1364-8152(99)00007-9
   Google Scholar
• Penman, H.L. (1948). “Natural evaporation from open water, bare soil and grass.” Proc. R. Soc. Lond., 193, 120–145.10.1098/rspa.1948.0037
   Web of Science ®Google Scholar
• Phukoetphim, P., Shamseldin, A.Y., and Melville, B.W. (2014). “Knowledge extraction from artificial neural networks for rainfall-runoff model combination systems.” J. Hydrol. Eng., 19, 1422–1429.10.1061/(ASCE)HE.1943-5584.0000941
   Web of Science ®Google Scholar
• Sudheer, K.P. (2005). “Knowledge extraction from trained neural network river flow models.” J. Hydrol. Eng., 10, 264–269.10.1061/(ASCE)1084-0699(2005)10:4(264)
   Web of Science ®Google Scholar
• Sudheer, K.P., and Jain, A. (2004). “Explaining the internal behaviour of artificial neural network river flow models.” Hydrol. Process., 18, 833–844.10.1002/(ISSN)1099-1085
   Web of Science ®Google Scholar
• Sudheer, K.P., and Jain, A. (2009). “Recent advances in knowledge extraction from neural network based hydrologic models.” ISH J. Hydraul. Eng., 15(sup1), 75–83.10.1080/09715010.2009.10514969
   Google Scholar
• The ASCE Task Committee. (2000). “Artificial neural networks in hydrology I: preliminary concepts.” J. Hydrol. Eng., 5(2), 115–123.
   Web of Science ®Google Scholar
• Wasserman, P.D. (1993). Advanced methods in neural computing, Van Nostrand Reinhold, New York, NY, 255.
   Google Scholar
• Wilby, R.L., Abrahart, R.J., and Dawson, C.W. (2003). “Detection of conceptual model rainfall-runoff processes inside an artificial neural network.” Hydrol. Sci. J., 48(2), 163–181. www.mahahp.gov.in10.1623/hysj.48.2.163.44699
   Web of Science ®Google Scholar