Genetic programming in water resources engineering: a state-of-the-art review

Gene Expression Programming: a New Adaptive Algorithm for Solving ProblemsPreprint

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Grammatical evolution

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A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

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A Representation for the Adaptive Generation of Simple Sequential Programs

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On inducing equations for vegetation resistance

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Grammar-based Genetic Programming: a survey

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A symbolic data-driven technique based on evolutionary polynomial regression

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Editorial

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Modeling rainfall-runoff process using soft computing techniques

Kişi, Ö., Shiri, J., & Tombul, M. (2012) · Computers & Geosciences · doi:10.1016/j.cageo.2012.07.001 · Cited by 271 · see citing works

GPTIPS 2: An Open-Source Software Platform for Symbolic Data Mining

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Handbook of Genetic Programming Applications

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A Genetic Programming Approach to Rainfall-Runoff Modelling

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A genetic programming approach to suspended sediment modelling

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The Entities of Gene Expression Programming

Ferreira, C. (2006) · Springer eBooks · doi:10.1007/3-540-32849-1_2 · Cited by 214 · see citing works

Genetic programming as a model induction engine

Babovic, V., & Keijzer, M. (2000) · Journal of Hydroinformatics · doi:10.2166/hydro.2000.0004 · Cited by 195 · see citing works

Genetic Programming to Predict Bridge Pier Scour

Azamathulla, H. M., Ghani, A. A., Zakaria, N. A., & Güven, A. (2009) · Journal of Hydraulic Engineering · doi:10.1061/(asce)hy.1943-7900.0000133 · Cited by 194 · see citing works

Multi-objective management of saltwater intrusion in coastal aquifers using genetic programming and modular neural network based surrogate models

Janardhanan, S., & Datta, B. (2010) · Journal of Hydrology · doi:10.1016/j.jhydrol.2010.08.023 · Cited by 193 · see citing works

Forecasting daily lake levels using artificial intelligence approaches

Kişi, Ö., Shiri, J., & Nikoofar, B. (2011) · Computers & Geosciences · doi:10.1016/j.cageo.2011.08.027 · Cited by 186 · see citing works

Landslide susceptibility mapping at Zonouz Plain, Iran using genetic programming and comparison with frequency ratio, logistic regression, and artificial neural network models

Nourani, V., Pradhan, B., Ghaffari, H., & Sharifi, S. S. (2013) · Natural Hazards · doi:10.1007/s11069-013-0932-3 · Cited by 182 · see citing works

GENETIC PROGRAMMING AND ITS APPLICATION IN REAL‐TIME RUNOFF FORECASTING 1

Khu, S. T., Liong, S., Babovic, V., Madsen, H., & Muttil, N. (2001) · JAWRA Journal of the American Water Resources Association · doi:10.1111/j.1752-1688.2001.tb00980.x · Cited by 178 · see citing works

Daily reference evapotranspiration modeling by using genetic programming approach in the Basque Country (Northern Spain)

Shiri, J., Kişi, Ö., Landeras, G., Rodríguez, J. J. L., Nazemi, A. H., & Stuyt, L. C. P. M. (2011) · Journal of Hydrology · doi:10.1016/j.jhydrol.2011.11.004 · Cited by 175 · see citing works

Prediction and simulation of monthly groundwater levels by genetic programming

Fallah-Mehdipour, E., Haddad, O. B., & Mariño, M. A. (2013) · Journal of Hydro-environment Research · doi:10.1016/j.jher.2013.03.005 · Cited by 174 · see citing works

Precipitation Forecasting Using Wavelet-Genetic Programming and Wavelet-Neuro-Fuzzy Conjunction Models

Kişi, Ö., & Shiri, J. (2011) · Water Resources Management · doi:10.1007/s11269-011-9849-3 · Cited by 167 · see citing works

Streamflow prediction using linear genetic programming in comparison with a neuro-wavelet technique

Mehr, A. D., Kahya, E., & Olyaie, E. (2013) · Journal of Hydrology · doi:10.1016/j.jhydrol.2013.10.003 · Cited by 165 · see citing works

Sea water level forecasting using genetic programming and comparing the performance with Artificial Neural Networks

Ghorbani, M. A., Khatibi, R. H., AYTEK, A., Makarynskyy, O., & Shiri, J. (2010) · Computers & Geosciences · doi:10.1016/j.cageo.2009.09.014 · Cited by 153 · see citing works

Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations

Shiri, J., & Kişi, Ö. (2010) · Computers & Geosciences · doi:10.1016/j.cageo.2010.11.010 · Cited by 149 · see citing works

Rainfall Runoff Modelling Based on Genetic Programming

Babovic, V., & Keijzer, M. (2002) · Hydrology research · doi:10.2166/nh.2002.0012 · Cited by 147 · see citing works

Extreme learning machine model for water network management

Sattar, A. M. A., Ertuğrul, Ö. F., Gharabaghi, B., McBean, E. A., & Cao, J. (2017) · Neural Computing and Applications · doi:10.1007/s00521-017-2987-7 · Cited by 145 · see citing works

Linear genetic programming for time-series modelling of daily flow rate

Güven, A. (2009) · Journal of Earth System Science · doi:10.1007/s12040-009-0022-9 · Cited by 142 · see citing works

Modelling the dynamics of the evapotranspiration process using genetic programming

Parasuraman, K., ELSHORBAGY, A. A., & Carey, S. K. (2007) · Hydrological Sciences Journal · doi:10.1623/hysj.52.3.563 · Cited by 141 · see citing works

A multi-model approach to analysis of environmental phenomena

Giustolisi, O., Doglioni, A., Savic, D. A., & Webb, B. (2006) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2005.12.026 · Cited by 138 · see citing works

Short-term streamflow forecasting with global climate change implications – A comparative study between genetic programming and neural network models

Makkeasorn, A., Chang, N., & Zhou, X. (2008) · Journal of Hydrology · doi:10.1016/j.jhydrol.2008.01.023 · Cited by 138 · see citing works

Real-Time Operation of Reservoir System by Genetic Programming

Fallah-Mehdipour, E., Haddad, O. B., & Mariño, M. A. (2012) · Water Resources Management · doi:10.1007/s11269-012-0132-z · Cited by 130 · see citing works

Gene expression models for prediction of longitudinal dispersion coefficient in streams

Sattar, A. M. A., & Gharabaghi, B. (2015) · Journal of Hydrology · doi:10.1016/j.jhydrol.2015.03.016 · Cited by 126 · see citing works

Evaluation of Climatic-Change Impacts on Multiobjective Reservoir Operation with Multiobjective Genetic Programming

Ashofteh, P., Haddad, O. B., & Loáiciga, H. A. (2015) · Journal of Water Resources Planning and Management · doi:10.1061/(asce)wr.1943-5452.0000540 · Cited by 125 · see citing works

Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

Ravansalar, M., Rajaee, T., & Kişi, Ö. (2017) · Journal of Hydrology · doi:10.1016/j.jhydrol.2017.04.018 · Cited by 123 · see citing works

River suspended sediment estimation by climatic variables implication: Comparative study among soft computing techniques

Kişi, Ö., & Shiri, J. (2012) · Computers & Geosciences · doi:10.1016/j.cageo.2012.02.007 · Cited by 122 · see citing works

An application of artificial intelligence for rainfall-runoff modeling

AYTEK, A., Asce, M., & Alp, M. (2008) · Journal of Earth System Science · doi:10.1007/s12040-008-0005-2 · Cited by 119 · see citing works

Forecasting monthly urban water demand using Extended Kalman Filter and Genetic Programming

Nasseri, M., Moeini, A., & Tabesh, M. (2010) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.12.087 · Cited by 116 · see citing works

Comparison of Gene Expression Programming with neuro-fuzzy and neural network computing techniques in estimating daily incoming solar radiation in the Basque Country (Northern Spain)

Landeras, G., Rodríguez, J. J. L., Kişi, Ö., & Shiri, J. (2012) · Energy Conversion and Management · doi:10.1016/j.enconman.2012.03.025 · Cited by 113 · see citing works

Using genetic programming to determine Chèzy resistance coefficient in corrugated channels

Giustolisi, O. (2004) · Journal of Hydroinformatics · doi:10.2166/hydro.2004.0013 · Cited by 112 · see citing works

Generalizability of Gene Expression Programming-based approaches for estimating daily reference evapotranspiration in coastal stations of Iran

Shiri, J., Sadraddini, A. A., Nazemi, A. H., Kişi, Ö., Landeras, G., Fard, A. F., & Martí, P. (2013) · Journal of Hydrology · doi:10.1016/j.jhydrol.2013.10.034 · Cited by 112 · see citing works

A survey of water level fluctuation predicting in Urmia Lake using support vector machine with firefly algorithm

Kişi, Ö., Shiri, J., Karimi, S., Shamshirband, S., Motamedi, S., Petković, D., & Hashim, R. (2015) · Applied Mathematics and Computation · doi:10.1016/j.amc.2015.08.085 · Cited by 110 · see citing works

Determination of Irrigation Allocation Policy under Climate Change by Genetic Programming

Ashofteh, P., Haddad, O. B., Akbari‐Alashti, H., & Mariño, M. A. (2014) · Journal of Irrigation and Drainage Engineering · doi:10.1061/(asce)ir.1943-4774.0000807 · Cited by 106 · see citing works

Hybrid Wavelet–Genetic Programming Approach to Optimize ANN Modeling of Rainfall–Runoff Process

Nourani, V., Komasi, M., & Alami, M. T. (2011) · Journal of Hydrologic Engineering · doi:10.1061/(asce)he.1943-5584.0000506 · Cited by 105 · see citing works

Statistical downscaling of watershed precipitation using Gene Expression Programming (GEP)

Hashmi, M. Z. U. R., Shamseldin, A. Y., & Melville, B. W. (2011) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2011.07.007 · Cited by 104 · see citing works

Modeling of Water Quality Parameters Using Data-Driven Models

Orouji, H., Haddad, O. B., Fallah-Mehdipour, E., & Mariño, M. A. (2013) · Journal of Environmental Engineering · doi:10.1061/(asce)ee.1943-7870.0000706 · Cited by 102 · see citing works

Daily pan evaporation modeling using linear genetic programming technique

Güven, A., & Kişi, Ö. (2010) · Irrigation Science · doi:10.1007/s00271-010-0225-5 · Cited by 101 · see citing works

Using gene expression programming in monthly reference evapotranspiration modeling: A case study in Egypt

Mattar, M. A. (2017) · Agricultural Water Management · doi:10.1016/j.agwat.2017.12.017 · Cited by 100 · see citing works

Gene-Expression Programming for Sediment Transport in Sewer Pipe Systems

Ghani, A. A., & Azamathulla, H. M. (2011) · Journal of Pipeline Systems Engineering and Practice · doi:10.1061/(asce)ps.1949-1204.0000076 · Cited by 98 · see citing works

Genetic Programming‐Based Empirical Model for Daily Reference Evapotranspiration Estimation

Güven, A., AYTEK, A., Yuce, M. I., & Aksoy, H. (2008) · CLEAN - Soil Air Water · doi:10.1002/clen.200800009 · Cited by 98 · see citing works

Genetic programming approach for flood routing in natural channels

Sivapragasam, C., Rathinasamy, M., & Venkatesh, V. (2007) · Hydrological Processes · doi:10.1002/hyp.6628 · Cited by 98 · see citing works

Quantification of the climate change-induced variations in Intensity–Duration–Frequency curves in the Canadian Prairies

Alam, M. S., & ELSHORBAGY, A. A. (2015) · Journal of Hydrology · doi:10.1016/j.jhydrol.2015.05.059 · Cited by 96 · see citing works

A gene–wavelet model for long lead time drought forecasting

Mehr, A. D., Kahya, E., & Özger, M. (2014) · Journal of Hydrology · doi:10.1016/j.jhydrol.2014.06.012 · Cited by 95 · see citing works

Wavelet neural networks and gene expression programming models to predict short-term soil temperature at different depths

Samadianfard, S., Asadi, E., Jarhan, S., Kazemi, H., Kheshtgar, S., Kişi, Ö., Sajjadi, S., & Manaf, A. A. (2017) · Soil and Tillage Research · doi:10.1016/j.still.2017.08.012 · Cited by 95 · see citing works

Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

Jothiprakash, V., & Magar, R. B. (2012) · Journal of Hydrology · doi:10.1016/j.jhydrol.2012.04.045 · Cited by 94 · see citing works

Monthly streamflow forecasting using continuous wavelet and multi-gene genetic programming combination

Hadi, S. J., & Tombul, M. (2018) · Journal of Hydrology · doi:10.1016/j.jhydrol.2018.04.036 · Cited by 94 · see citing works

Prediction of flow duration curves for ungauged basins

Atieh, M., Taylor, G. W., Sattar, A. M. A., & Gharabaghi, B. (2017) · Journal of Hydrology · doi:10.1016/j.jhydrol.2016.12.048 · Cited by 91 · see citing works

Runoff forecasting using hybrid Wavelet Gene Expression Programming (WGEP) approach

Shoaib, M., Shamseldin, A. Y., Melville, B. W., & Khan, M. M. (2015) · Journal of Hydrology · doi:10.1016/j.jhydrol.2015.04.072 · Cited by 88 · see citing works

Genetic Programming for the Downscaling of Extreme Rainfall Events on the East Coast of Peninsular Malaysia

Pour, S. H., Harun, S. B., & Shahid, S. (2014) · Atmosphere · doi:10.3390/atmos5040914 · Cited by 88 · see citing works

Soil temperature modeling at different depths using neuro-fuzzy, neural network, and genetic programming techniques

Kişi, Ö., Sanikhani, H., & Çobaner, M. (2016) · Theoretical and Applied Climatology · doi:10.1007/s00704-016-1810-1 · Cited by 88 · see citing works

Discharge forecasting using an Online Sequential Extreme Learning Machine (OS-ELM) model: A case study in Neckar River, Germany

Yadav, B., Ch, S., Mathur, S., & Adamowski, J. (2016) · Measurement · doi:10.1016/j.measurement.2016.06.042 · Cited by 88 · see citing works

Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

Kashid, S. S., & Maity, R. (2012) · Journal of Hydrology · doi:10.1016/j.jhydrol.2012.05.033 · Cited by 87 · see citing works

Gene Expression Models for the Prediction of Longitudinal Dispersion Coefficients in Transitional and Turbulent Pipe Flow

Sattar, A. M. A. (2013) · Journal of Pipeline Systems Engineering and Practice · doi:10.1061/(asce)ps.1949-1204.0000153 · Cited by 87 · see citing works

Developing reservoir operational decision rule by genetic programming

Fallah-Mehdipour, E., Haddad, O. B., & Mariño, M. A. (2012) · Journal of Hydroinformatics · doi:10.2166/hydro.2012.140 · Cited by 86 · see citing works

Data mining in hydrology

Babovic, V. (2005) · Hydrological Processes · doi:10.1002/hyp.5862 · Cited by 86 · see citing works

Estimation of daily global solar radiation using wavelet regression, ANN, GEP and empirical models: A comparative study of selected temperature-based approaches

Sharifi, S. S., Rezaverdinejad, V., & Nourani, V. (2016) · Journal of Atmospheric and Solar-Terrestrial Physics · doi:10.1016/j.jastp.2016.10.008 · Cited by 83 · see citing works

Dimensionally aware genetic programming

Keijzer, M., & Babovic, V. (1999) · Cited by 79 · see citing works

Determination of the unit hydrograph of a typical urban basin using genetic programming and artificial neural networks

Rabuñal, J. R., Puertas, J., Suárez, J., & Rivero, D. (2006) · Hydrological Processes · doi:10.1002/hyp.6250 · Cited by 78 · see citing works

Comparison of three artificial intelligence techniques for discharge routing

Khatibi, R. H., Ghorbani, M. A., Kashani, M. H., & Kişi, Ö. (2011) · Journal of Hydrology · doi:10.1016/j.jhydrol.2011.03.007 · Cited by 78 · see citing works

Prediction and modeling of the rainfall-runoff transformation of a typical urban basin using ann and gp

Dorado, J., Rabuñal, J. R., Pazos, A., Rivero, D., Santos, A., & Puertas, J. (2003) · Applied Artificial Intelligence · doi:10.1080/713827142 · Cited by 77 · see citing works

Prediction of hourly actual evapotranspiration using neural networks, genetic programming, and statistical models

Izadifar, Z., & ELSHORBAGY, A. A. (2010) · Hydrological Processes · doi:10.1002/hyp.7771 · Cited by 75 · see citing works

Genetic Programming in Groundwater Modeling

Fallah-Mehdipour, E., Haddad, O. B., & Mariño, M. A. (2014) · Journal of Hydrologic Engineering · doi:10.1061/(asce)he.1943-5584.0000987 · Cited by 75 · see citing works

Modeling Water-Quality Parameters Using Genetic Algorithm–Least Squares Support Vector Regression and Genetic Programming

Haddad, O. B., Soleimani, S., & Loáiciga, H. A. (2017) · Journal of Environmental Engineering · doi:10.1061/(asce)ee.1943-7870.0001217 · Cited by 75 · see citing works

A Pareto-optimal moving average-multigene genetic programming model for rainfall-runoff modelling

Mehr, A. D., & Nourani, V. (2017) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2017.03.004 · Cited by 75 · see citing works

An improved gene expression programming model for streamflow forecasting in intermittent streams

Mehr, A. D. (2018) · Journal of Hydrology · doi:10.1016/j.jhydrol.2018.06.049 · Cited by 73 · see citing works

A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

Mehr, A. D., & Kahya, E. (2017) · Journal of Hydrology · doi:10.1016/j.jhydrol.2017.04.045 · Cited by 72 · see citing works

A Compiling Genetic Programming System that Directly Manipulates the Machine Code

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Quantile-Based Downscaling of Precipitation Using Genetic Programming: Application to IDF Curves in Saskatoon

Hassanzadeh, E., Nazemi, A., & ELSHORBAGY, A. A. (2013) · Journal of Hydrologic Engineering · doi:10.1061/(asce)he.1943-5584.0000854 · Cited by 71 · see citing works

Estimating Saturated Hydraulic Conductivity Using Genetic Programming

Parasuraman, K., ELSHORBAGY, A. A., & Si, B. (2007) · Soil Science Society of America Journal · doi:10.2136/sssaj2006.0396 · Cited by 71 · see citing works

Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

Mehdizadeh, S., Behmanesh, J., & Khalili, K. (2016) · Journal of Atmospheric and Solar-Terrestrial Physics · doi:10.1016/j.jastp.2016.06.006 · Cited by 71 · see citing works

Velocity predictions in compound channels with vegetated floodplains using genetic programming

Harris, E. L., Babovic, V., & Falconer, R. A. (2003) · International Journal of River Basin Management · doi:10.1080/15715124.2003.9635198 · Cited by 70 · see citing works

Downscaling daily extreme temperatures with genetic programming

Coulibaly, P. (2004) · Geophysical Research Letters · doi:10.1029/2004gl020075 · Cited by 69 · see citing works

Neuro-Fuzzy GMDH Approach to Predict Longitudinal Dispersion in Water Networks

Najafzadeh, M., & Sattar, A. M. A. (2015) · Water Resources Management · doi:10.1007/s11269-015-0936-8 · Cited by 67 · see citing works

The evolution of equations from hydraulic data Part I: Theory

Babovic, V., & Abbott, M. B. (1997) · Journal of Hydraulic Research · doi:10.1080/00221689709498420 · Cited by 65 · see citing works

Estimation of Suspended Sediment Yield in Natural Rivers Using Machine-coded Linear Genetic Programming

Güven, A., & Kişi, Ö. (2010) · Water Resources Management · doi:10.1007/s11269-010-9721-x · Cited by 65 · see citing works

A hybrid artificial intelligence model for river flow forecasting

Fajardo-Toro, C. H., Gómez-Meire, S., Gálvez, J. F., & Fdez‐Riverola, F. (2013) · Applied Soft Computing · doi:10.1016/j.asoc.2013.04.014 · Cited by 63 · see citing works

Regional-Specific Numerical Models of Evapotranspiration Using Gene-Expression Programming Interface in Sahel

Traore, S. B., & Güven, A. (2012) · Water Resources Management · doi:10.1007/s11269-012-0149-3 · Cited by 62 · see citing works

Gene expression models for prediction of dam breach parameters

Sattar, A. M. A. (2013) · Journal of Hydroinformatics · doi:10.2166/hydro.2013.084 · Cited by 62 · see citing works

Flow discharge prediction in compound channels using linear genetic programming

Azamathulla, H. M., & Zahiri, A. (2012) · Journal of Hydrology · doi:10.1016/j.jhydrol.2012.05.065 · Cited by 61 · see citing works

Impervious surfaces and sewer pipe effects on stormwater runoff temperature

Sabouri, F., Gharabaghi, B., Mahboubi, A. A., & McBean, E. A. (2013) · Journal of Hydrology · doi:10.1016/j.jhydrol.2013.08.016 · Cited by 61 · see citing works

Comparison of multi-gene genetic programming and dynamic evolving neural-fuzzy inference system in modeling pan evaporation

Eray, O., Mert, C., & Kişi, Ö. (2017) · Hydrology research · doi:10.2166/nh.2017.076 · Cited by 61 · see citing works

Prediction of algal blooms using genetic programming

Sivapragasam, C., Muttil, N., Muthukumar, S., & Arun, V. M. (2010) · Marine Pollution Bulletin · doi:10.1016/j.marpolbul.2010.05.020 · Cited by 60 · see citing works

Estimation of daily dew point temperature using genetic programming and neural networks approaches

Shiri, J., Kim, S., & Kişi, Ö. (2013) · Hydrology research · doi:10.2166/nh.2013.229 · Cited by 60 · see citing works

Declarative and Preferential Bias in GP-based Scientific Discovery

Keijzer, M., & Babovic, V. (2002) · Genetic Programming and Evolvable Machines · doi:10.1023/a:1014596120381 · Cited by 59 · see citing works

Event-based total suspended sediment particle size distribution model

Thompson, J., Sattar, A. M. A., Gharabaghi, B., & Warner, R. C. (2016) · Journal of Hydrology · doi:10.1016/j.jhydrol.2016.02.056 · Cited by 59 · see citing works

Prediction of Timing of Watermain Failure Using Gene Expression Models

Sattar, A. M. A., Gharabaghi, B., & McBean, E. A. (2016) · Water Resources Management · doi:10.1007/s11269-016-1241-x · Cited by 59 · see citing works

Application of gene expression programming to predict daily dew point temperature

Mehdizadeh, S., Behmanesh, J., & Khalili, K. (2016) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2016.10.181 · Cited by 59 · see citing works

Chaos-based multigene genetic programming: A new hybrid strategy for river flow forecasting

Ghorbani, M. A., Khatibi, R. H., Mehr, A. D., & Asadi, H. (2018) · Journal of Hydrology · doi:10.1016/j.jhydrol.2018.04.054 · Cited by 59 · see citing works

Season Algorithm-Multigene Genetic Programming: A New Approach for Rainfall-Runoff Modelling

Mehr, A. D., & Nourani, V. (2018) · Water Resources Management · doi:10.1007/s11269-018-1951-3 · Cited by 58 · see citing works

Evapotranspiration Modeling Using Linear Genetic Programming Technique

Kişi, Ö., & Güven, A. (2010) · Journal of Irrigation and Drainage Engineering · doi:10.1061/(asce)ir.1943-4774.0000244 · Cited by 57 · see citing works

Multigene genetic programming for sediment transport modeling in sewers for conditions of non-deposition with a bed deposit

Safari, M. J. S., & Mehr, A. D. (2018) · International Journal of Sediment Research · doi:10.1016/j.ijsrc.2018.04.007 · Cited by 57 · see citing works

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

Kashid, S. S., Ghosh, S., & Maity, R. (2010) · Journal of Hydrology · doi:10.1016/j.jhydrol.2010.10.004 · Cited by 56 · see citing works

Toward improving the reliability of hydrologic prediction: Model structure uncertainty and its quantification using ensemble‐based genetic programming framework

Parasuraman, K., & ELSHORBAGY, A. A. (2008) · Water Resources Research · doi:10.1029/2007wr006451 · Cited by 53 · see citing works

Introducing knowledge into learning based on genetic programming

Babovic, V. (2009) · Journal of Hydroinformatics · doi:10.2166/hydro.2009.041 · Cited by 53 · see citing works

Linear genetic programming application for successive-station monthly streamflow prediction

Mehr, A. D., Kahya, E., & Yerdelen, C. (2014) · Computers & Geosciences · doi:10.1016/j.cageo.2014.04.015 · Cited by 53 · see citing works

New Approaches for Estimation of Monthly Rainfall Based on GEP-ARCH and ANN-ARCH Hybrid Models

Mehdizadeh, S., Behmanesh, J., & Khalili, K. (2017) · Water Resources Management · doi:10.1007/s11269-017-1825-0 · Cited by 52 · see citing works

Proceedings of the 2nd Annual Conference on Genetic and Evolutionary Computation

Whitley, L. D., Goldberg, D. E., Cantú‐Paz, E., Spector, L. C., & Parmee, I. C. (2000) · Cited by 52 · see citing works

Development of genetic programming-based model for predicting oyster norovirus outbreak risks

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Simulation of the depth scouring downstream sluice gate: The validation of newly developed data-intelligent models

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A Hybrid Model for Streamflow Forecasting in the Basin of Euphrates

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Boosted artificial intelligence model using improved alpha-guided grey wolf optimizer for groundwater level prediction: Comparative study and insight for federated learning technology

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A New Benchmark on Machine Learning Methodologies for Hydrological Processes Modelling: A Comprehensive Review for Limitations and Future Research Directions

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Pan Evaporation Estimation in Uttarakhand and Uttar Pradesh States, India: Validity of an Integrative Data Intelligence Model

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Genetic programming for hydrological applications: to model or to forecast that is the question

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A comprehensive uncertainty analysis of model-estimated longitudinal and lateral dispersion coefficients in open channels

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A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting

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Accelerating hydrodynamic simulations of urban drainage systems with physics-guided machine learning

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Parameters Identification of a Permanent Magnet DC Motor: A Review

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New optimization strategies for SWMM modeling of stormwater quality applications in urban area

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A new evolutionary time series model for streamflow forecasting in boreal lake-river systems

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Modeling of pan evaporation based on the development of machine learning methods

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Data filtering methods for SARS-CoV-2 wastewater surveillance

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MSGP-LASSO: An improved multi-stage genetic programming model for streamflow prediction

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Earth skin temperature long-term prediction using novel extended Kalman filter integrated with Artificial Intelligence models and information gain feature selection

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Sediment transport modeling in open channels using neuro-fuzzy and gene expression programming techniques

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Buoyant Jets in Cross-Flows: Review, Developments, and Applications

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A Comparative Analysis of Data‐Driven Empirical and Artificial Intelligence Models for Estimating Infiltration Rates

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Drought Index Prediction Using Data Intelligent Analytic Models: A Review

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Wavelet Packet-Genetic Programming: A New Model for Meteorological Drought Hindcasting

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Point-based and probabilistic electricity demand prediction with a Neural Facebook Prophet and Kernel Density Estimation model

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Predicting nanocomposite binder improved unsaturated soil UCS using genetic programming

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Optimization of Extreme Learning Machine with Metaheuristic Algorithms for Modelling Water Quality Parameters of Tamburawa Water Treatment Plant in Nigeria

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Application of Soft Computing Techniques for Particle Froude Number Estimation in Sewer Pipes

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Steam Condensation Heat Transfer in the Presence of Noncondensable Gases (NCGs) in Nuclear Power Plants (NPPs): A Comprehensive Review of Fundamentals, Current Status, and Prospects for Future Research

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Regression models for sediment transport in tropical rivers

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A Semi-empirical Approach Based on Genetic Programming for the Study of Biophysical Controls on Diameter-Growth of Fagus orientalis in Northern Iran

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A systematic review of explainability in computational intelligence for optimization

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Evaluating the application of data-driven intelligent methods to estimate discharge over triangular arced labyrinth weir

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Generating Fake News Detection Model Using A Two-Stage Evolutionary Approach

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The Applications of Soft Computing Methods for Seepage Modeling: A Review

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Trend analysis of temperature data using innovative polygon trend analysis and modeling by gene expression programming

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(AI) in Infrastructure Projects—Gap Study

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Prediction of Potential Evapotranspiration via Machine Learning and Deep Learning for Sustainable Water Management in the Murat River Basin

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Pipe failure prediction of wastewater network using genetic programming: Proposing three approaches

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Reinforcing long lead time drought forecasting with a novel hybrid deep learning model: a case study in Iran

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