Prediction of Groundwater Level in Ardebil Plain Using Support Vector Regression and M5 Tree Model

Regional bivariate modeling of droughts using L-comoments and copulas

(2016) Amin Abdi et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

Evaluating groundwater level fluctuation by support vector regression and neuro-fuzzy methods: a comparative study

(2015) Mohammad Mirzavand et al.   NATURAL HAZARDS

Investigation of spatial and temporal variability of precipitation in Iran over the last half century

(2015) Keivan Khalili et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

A Comparative Study of Artificial Neural Networks, Support Vector Machines and Adaptive Neuro Fuzzy Inference System for Forecasting Groundwater Levels near Lake Okeechobee, Florida

(2015) Yicheng Gong et al.   WATER RESOURCES MANAGEMENT

Use of Machine Learning Methods to Reduce Predictive Error of Groundwater Models

(2014) Tianfang Xu et al.   Groundwater

Ground water quality classification by decision tree method in Ardebil region, Iran

(2013) S. Mehdi Saghebian et al.   Arabian Journal of Geosciences

Analysis of meteorological drought in northwest Iran using the Joint Deficit Index

(2013) Rasoul Mirabbasi et al.   JOURNAL OF HYDROLOGY

M5 model tree application in daily river flow forecasting in Sohu Stream, Turkey

(2013) M. Taghi Sattari et al.   Water Resources

Trend analysis of groundwater using non-parametric methods (case study: Ardabil plain)

(2012) Farnaz Daneshvar Vousoughi et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

M5 model tree based modelling of reference evapotranspiration

(2009) Mahesh Pal et al.   HYDROLOGICAL PROCESSES

Comparative Study of SVMs and ANNs in Aquifer Water Level Prediction

(2009) Mohsen Behzad et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING