Abstract
As a computational method with impressive performance over traditional methods, Artificial Intelligence (AI) has recently gained great attention. It is a consortium of different soft-computational methodologies including artificial neural networks (ANNs), Fuzzy Logic (FL), Wavelet Transformation (WT) and so forth. AI recently begun to explain complex and non-linear problems in geoscience and hydrology in a clear and satisfactory manner. The combination of one and more approaches has created, rather than applying one approach, new categories such as Neuro-Fuzzy (NF), which are more effective than distinct approaches. Considering the recognition and huge application and promotion of AI procedures in geoscience and hydrology since last few years, it would be an vital chore to deduce the distinctive new use of the AI techniques in groundwater investigation. It was therefore our goal to exhibit the use of AI to take care of the perplexing and nonlinear issues in the field of groundwater research. In this chapter we have attempted to emphasize the learning of individual and hybrid AI techniques in groundwater studies, introduce and apply them. We mainly described different individual and combined soft-computing tools like Fuzzy logic, Sugeno fuzzy logic, Neurofuzzy, Gradient-based groundwater model, Artificial Neural Network, Support Vector Machine, and Wavelet transform to assess and monitor groundwater resources. Long-term applications and advancement of AI procedure for precise appraisal of groundwater assets is additionally proposed.
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Bhunia, G.S., Shit, P.K., Adhikary, P.P. (2021). Concept of Artificial Intelligence and Its Applications in Groundwater Spatial Studies. In: Adhikary, P.P., Shit, P.K., Santra, P., Bhunia, G.S., Tiwari, A.K., Chaudhary, B.S. (eds) Geostatistics and Geospatial Technologies for Groundwater Resources in India. Springer Hydrogeology. Springer, Cham. https://doi.org/10.1007/978-3-030-62397-5_3
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