Genetic programming based monthly groundwater level forecast models with uncertainty quantification

Modeling Earth Systems and Environment ◽

10.1007/s40808-016-0083-0 ◽

2016 ◽

Vol 2 (1) ◽

Author(s):

K. S. Kasiviswanathan ◽

S. Saravanan ◽

M. Balamurugan ◽

K. Saravanan

Keyword(s):

Genetic Programming ◽

Uncertainty Quantification ◽

Groundwater Level ◽

Forecast Models ◽

Groundwater Level Forecast

Download Full-text

Groundwater Level Forecast Via a Discrete Space-State Modelling Approach as a Surrogate to Complex Groundwater Simulation Modelling

Water Resources Management ◽

10.1007/s11269-021-02787-6 ◽

2021 ◽

Author(s):

Dilip Kumar Roy ◽

Sujit Kumar Biswas ◽

Kowshik Kumar Saha ◽

Khandakar Faisal Ibn Murad

Keyword(s):

Groundwater Level ◽

Simulation Modelling ◽

Discrete Space ◽

Groundwater Simulation ◽

Space State ◽

Groundwater Level Forecast ◽

Modelling Approach

Download Full-text

Groundwater level prediction using genetic programming: the importance of precipitation data and weather station location on model accuracy

Environmental Earth Sciences ◽

10.1007/s12665-019-8776-0 ◽

2019 ◽

Vol 79 (1) ◽

Author(s):

Mahmood Sadat-Noori ◽

William Glamore ◽

Danial Khojasteh

Keyword(s):

Genetic Programming ◽

Groundwater Level ◽

Precipitation Data ◽

Weather Station ◽

Model Accuracy ◽

Station Location ◽

Groundwater Level Prediction

Download Full-text

Assessing the Utility of Rainfall Forecasts for Weekly Groundwater Level Forecast in Tampa Bay Region, Florida

Journal of The Korean Society of Agricultural Engineers ◽

10.5389/ksae.2013.55.6.001 ◽

2013 ◽

Vol 55 (6) ◽

pp. 1-9

Author(s):

Syewoon Hwang ◽

Tirusew Asefa ◽

Seungwoo Chang

Keyword(s):

Groundwater Level ◽

Tampa Bay ◽

Groundwater Level Forecast

Download Full-text

Analysis and prediction of groundwater level time series with Autoregressive Linear Models

Rendiconti online della Società Geologica Italiana ◽

10.3301/rol.2016.59 ◽

2016 ◽

Vol 39 ◽

pp. 109-112

Author(s):

Mirko Ginocchi ◽

Giovanni Franco Crosta ◽

Marco Rotiroti ◽

Tullia Bonomi

Keyword(s):

Time Series ◽

Groundwater Level ◽

Download Full-text

Parameter Estimation and Uncertainty Quantification in Water Resources Modeling

10.3389/978-2-88963-674-7 ◽

2020 ◽

Keyword(s):

Parameter Estimation ◽

Water Resources ◽

Uncertainty Quantification

Download Full-text

Practical Usages of a Neuro-genetic Programming for Short-term Water Level Prediction

International Conference on Biological, Environment and Food Engineering (BEFE-2014) August 4-5, 2014 Bali (Indonesia) ◽

10.15242/iicbe.c814068 ◽

2014 ◽

Keyword(s):

Genetic Programming ◽

Water Level ◽

Water Level Prediction

Download Full-text

Probabilistic Model Building Genetic Programming based on Estimation of Bayesian Network

Transactions of the Japanese Society for Artificial Intelligence ◽

10.1527/tjsai.22.37 ◽

2007 ◽

Vol 22 ◽

pp. 37-47 ◽

Author(s):

Yoshihiko Hasegawa ◽

Hitoshi Iba

Keyword(s):

Genetic Programming ◽

Bayesian Network ◽

Probabilistic Model ◽

Download Full-text

Automatic Generation of English-Japanese Translation Pattern Utilizing Genetic Programming Technique

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.130.1078 ◽

2010 ◽

Vol 130 (6) ◽

pp. 1078-1088

Author(s):

Koki Matsumura ◽

Yuji Tamekuni ◽

Shuhei Kimura

Keyword(s):

Genetic Programming ◽

Automatic Generation ◽

Programming Technique ◽

Japanese Translation

Download Full-text

UNCERTAINTY QUANTIFICATION TOWARDS FILTERING OPTIMIZATION IN SCENE MATCHING AIDED NAVIGATION SYSTEMS

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2016016561 ◽

2016 ◽

Vol 6 (2) ◽

pp. 127-140

Author(s):

Shengdi Zhang ◽

Xiaojun Duan ◽

Lijun Peng

Keyword(s):

Uncertainty Quantification ◽

Navigation Systems ◽

Download Full-text

INVERSE UNCERTAINTY QUANTIFICATION OF A CELL MODEL USING A GAUSSIAN PROCESS METAMODEL

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2020033186 ◽

2020 ◽

Vol 10 (4) ◽

pp. 333-349

Author(s):

Kevin de Vries ◽

Anna Nikishova ◽

Benjamin Czaja ◽

Gábor Závodszky ◽

Alfons G. Hoekstra

Keyword(s):

Gaussian Process ◽

Uncertainty Quantification ◽

Download Full-text