Long-term prediction of rainfalls is one of the most challenging tasks in stochastic hydrology owing to the highly random characteristics of rainfall events. In this paper, a novel approach is adopted to develop a hybrid ...

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 ...

Frame optimization that contains highly non-linear and irregular functions and discrete design variables is one of the most challenging optimization problems. Therefore, gradient-based optimization techniques cannot be ...

Location selection for offshore wind farms is a major challenge for renewable energy policy, marine spatial planning, and environmental conservation. This selection constitutes a multi-criteria decision-making problem, ...

In recent decades, self-compacting concrete (SCC) has gradually gained popularity based on its unique workability without any internal and external vibration. SCC development must ensure an acceptable level of balance ...

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 ...

The principle purpose of the current study is to hybridize firefly algorithm (FA) as a nature-inspired meta-heuristic developed based on the flashing patterns and biogeography-based optimization (BBO) to present a qualified ...