Turbulence in two-phase flows drives many important natural and engineering processes, from geophysical to nuclear power generation. Strong interphase coupling between the carrier fluid disperse phase precludes use of classical turbulence models developed for single-phase flows. In recent years, there has been an explosion machine learning techniques closure modeling, though rely on augmenting ...

In this paper one of the new generation soft computing technique that is known as Gene Expression Programming (GEP) is used to develop a meta-model for the multiobjective design of a hypothetical production line. The developed meta-model is used to optimize production line design with Multiple Objective Tabu Search algorithm (MOTS). It is found out that GEP and MOTS can be effectively used to s...

The effective thermal conductivity (ETC) of soil is an essential parameter for the design and unhindered operation underground energy transportation storage systems. Various experimental, empirical, semi-empirical, mathematical, numerical methods have been tried in past, but lack either accuracy or are computationally cumbersome. recent developments computer science provided a new computational...

In this paper, an improved GEP(Gene Expression Programming based on Block Strategy, BS-GEP) is proposed in consideration of the characteristics of software reliability growth models, on which a new software reliability modeling method is formed. Block strategy is the key point of BS-GEP, in which the population is divided into several blocks according to the individual fitness of each generatio...

This paper studies the time complexity of gene expression programming based on maintaining elitist (MEGEP). Using the theory of Markov chain and the technique of artificial fitness level, the properties of transition matrices of ME-GEP are analyzed. Based on the properties, the upper and lower bounds of the average time complexity of ME-GEP are obtained. Furthermore, the upper bound is estimate...

Abstract Infiltration plays a fundamental role in streamflow, groundwater recharge, subsurface flow, and surface water quality quantity. This study includes comparative analysis of the two machine learning techniques, M5P model tree (M5P) Gene Expression Programming (GEP), predictions infiltration characteristics. The models were trained tested using 7 combination (CMB1 – CMB7) input parameters...

This paper proposes a decision support system for tactical air combat environment using a combination of unsupervised learning for clustering the data and an ensemble of three well-known genetic programming techniques to classify the different decision regions accurately. The genetic programming techniques used are: Linear Genetic programming (LGP), Multi-Expression Programming (MEP) and Gene E...

Abstract The evaluation of groundwater quality plays an important role in the management groundwater. main objectives present work are to develop a novel soft computing framework including Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANFIS (WANFIS), Gene Expression Programming (GEP), and Wavelet-GEP (WGEP) for temporal spatial estimation electrical conductivity (EC) East Azerbaijan pr...