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An improved gene expression programming model for streamflow forecasting in intermittent streams
(Elsevier, 2018)
Skilful forecasting of monthly streamflow in intermittent rivers is a challenging task in stochastic hydrology. In this study, genetic algorithm (GA) was combined with gene expression programming (GEP) as a new hybrid model ...
Assigning convenient paths by an approach of dynamic programming
(1st Mediterranean International Conference of Pure and Applied Mathematics and Related Areas 2018 (MICOPAM 2018), 2018)
For many decades, mathematical models and methodologies have been essential in order to provide the understanding of countless engineering processes and technologies. Using mathematical models in many academic research, ...
Facility location determined by an iterative technique
(1st Mediterranean International Conference of Pure and Applied Mathematics and Related Areas 2018 (MICOPAM 2018), 2018)
For many decades, mathematical models and methodologies have been essential in order to provide the understanding of countless engineering processes and technologies. Using mathematical models in many academic research, ...
Multigene genetic programming for sediment transport modeling in sewers for conditions of non-deposition with a bed deposit
(Elsevier, 2018)
It is known that construction of large sewers based on consideration of flow with non-deposition without a bed deposit is not economical. Sewer design based on consideration of flow with non-deposition with a bed deposit ...
Trend analysis of hydroclimatological variables in Urmia lake basin using hybrid wavelet Mann–Kendall and Şen tests
(Springer-Verlag, 2018)
This paper investigates monthly, seasonal, and annual trends in rainfall, streamflow, temperature, and humidity amounts at Urmia lake (UL) basin and analyzes the interaction between these variables and UL’s water level ...
Season algorithm-multigene genetic programming: a new approach for rainfall-runoff modelling
(Springer Netherlands, 2018)
Genetic programming (GP) is recognized as a robust machine learning method for rainfall-runoff modelling. However, it may produce lagged forecasts if autocorrelation feature of runoff series is not taken carefully into ...
Genetic programming in water resources engineering: a state-of-the-art review
(Elsevier, 2018)
The state-of-the-art genetic programming (GP) method is an evolutionary algorithm for automatic generation of computer programs. In recent decades, GP has been frequently applied on various kind of engineering problems and ...
Chaos-based multigene genetic programming: a new hybrid strategy for river flow forecasting
(Elsevier, 2018)
Chaos theory is integrated with Multi-Gene Genetic Programming (MGGP) engine as a new hybrid model for river flow forecasting. This is to be referred to as Chaos-MGGP and its performance is tested using daily historic flow ...