Spatial mapping of groundwater springs potentiality using grid search-based and genetic algorithm-based support vector regression

In this study, groundwater springs potentiality maps were prepared using a novel integrated model, support vector regression (SVR) with genetic algorithm (GA), for the Jerash and Ajloun region, Jor...

[1]  I. Moore,et al.  Digital terrain modelling: A review of hydrological, geomorphological, and biological applications , 1991 .

[2]  P. J. Chilton,et al.  Groundwater: the processes and global significance of aquifer degradation. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[3]  Biswajeet Pradhan,et al.  Novel Hybrid Integration Approach of Bagging-Based Fisher’s Linear Discriminant Function for Groundwater Potential Analysis , 2019, Natural Resources Research.

[4]  I. Moore,et al.  Sediment Transport Capacity of Sheet and Rill Flow: Application of Unit Stream Power Theory , 1986 .

[5]  Darrell Whitley,et al.  A genetic algorithm tutorial , 1994, Statistics and Computing.

[6]  Hamid Reza Pourghasemi,et al.  Groundwater qanat potential mapping using frequency ratio and Shannon’s entropy models in the Moghan watershed, Iran , 2015, Earth Science Informatics.

[7]  R. Bras,et al.  Modeling the effects of vegetation‐erosion coupling on landscape evolution , 2004 .

[8]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[9]  A. Abed.  Depositional environments of the early cretaceous Kurnub (Hathira) sandstones, North Jordan , 1982 .

[10]  Hossein Shafizadeh-Moghadam,et al.  USING MULTIVARIATE ADAPTIVE REGRESSION SPLINE AND ARTIFICIAL NEURAL NETWORK TO SIMULATE URBANIZATION IN MUMBAI, INDIA , 2015 .

[11]  A. Al-Abadi,et al.  A GIS-based combining of frequency ratio and index of entropy approaches for mapping groundwater availability zones at Badra–Al Al-Gharbi–Teeb areas, Iraq , 2016, Sustainable Water Resources Management.

[12]  Sayan Mukherjee,et al.  Choosing Multiple Parameters for Support Vector Machines , 2002, Machine Learning.

[13]  M. Israil,et al.  Groundwater-recharge estimation using a surface electrical resistivity method in the Himalayan foothill region, India , 2006 .

[14]  V. Singh,et al.  Mapping Groundwater Potential Using a Novel Hybrid Intelligence Approach , 2018, Water Resources Management.

[15]  Seyed Amir Naghibi,et al.  Application of Support Vector Machine, Random Forest, and Genetic Algorithm Optimized Random Forest Models in Groundwater Potential Mapping , 2017, Water Resources Management.

[16]  H. S. Lim,et al.  Regional prediction of groundwater potential mapping in a multifaceted geology terrain using GIS-based Dempster–Shafer model , 2015, Arabian Journal of Geosciences.

[17]  Hamid Reza Pourghasemi,et al.  A comparison between ten advanced and soft computing models for groundwater qanat potential assessment in Iran using R and GIS , 2018, Theoretical and Applied Climatology.

[18]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[19]  Timothy B. Minor,et al.  Groundwater Assessment Using Remote Sensing And GIS In A Rural Groundwater Project In Ghana: Lessons Learned , 1996 .

[20]  D. Bui,et al.  Spatial prediction of groundwater spring potential mapping based on an adaptive neuro-fuzzy inference system and metaheuristic optimization , 2018, Hydrology and Earth System Sciences.

[21]  Saro Lee,et al.  GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea , 2011 .

[22]  Hyung-Sup Jung,et al.  GIS-based groundwater potential mapping using artificial neural network and support vector machine models: the case of Boryeong city in Korea , 2018 .

[23]  Wei Chen,et al.  Spatial prediction of groundwater potentiality using ANFIS ensembled with teaching-learning-based and biogeography-based optimization , 2019, Journal of Hydrology.

[24]  Seyed Amir Naghibi,et al.  A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping , 2017 .

[25]  A. Ozdemir.  GIS-based groundwater spring potential mapping in the Sultan Mountains (Konya, Turkey) using frequency ratio, weights of evidence and logistic regression methods and their comparison , 2011 .

[26]  Abdel Rahman Al-Shabeeb,et al.  Delineating groundwater potential zones within the Azraq Basin of Central Jordan using multi-criteria GIS analysis , 2018, Groundwater for Sustainable Development.

[27]  Barnali M. Dixon,et al.  Optimization of DRASTIC method by supervised committee machine artificial intelligence to assess groundwater vulnerability for Maragheh–Bonab plain aquifer, Iran , 2013 .

[28]  Bernhard Schölkopf,et al.  A tutorial on support vector regression , 2004, Stat. Comput..

[29]  Hamid Reza Pourghasemi,et al.  Assessment of a data-driven evidential belief function model and GIS for groundwater potential mapping in the Koohrang Watershed, Iran , 2015 .

[30]  Keith Beven,et al.  TOPMODEL : a critique. , 1997 .

[31]  Seyed Amir Naghibi,et al.  GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran , 2015, Environmental Monitoring and Assessment.

[32]  Wei Chen,et al.  GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models. , 2018, The Science of the total environment.

[33]  Biswajeet Pradhan,et al.  Application of probabilistic-based frequency ratio model in groundwater potential mapping using remote sensing data and GIS , 2014, Arabian Journal of Geosciences.

[34]  Mahdi Hasanlou,et al.  Integration of genetic algorithm and multiple kernel support vector regression for modeling urban growth , 2017, Comput. Environ. Urban Syst..

[35]  H. Pourghasemi,et al.  Application of GIS-based data driven random forest and maximum entropy models for groundwater potential mapping: A case study at Mehran Region, Iran , 2016 .

[36]  A. Al-Fugara.  Comparison and Validation of the Recent Freely Available DEMs over Parts of the Earth’s Lowest Elevation Area: Dead Sea, Jordan , 2015 .

[37]  Keith Beven,et al.  A dynamic TOPMODEL , 2001 .

[38]  D. H. Pilgrim,et al.  Problems of rainfall-runoff modelling in arid and semiarid regions , 1988 .