In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

be described adequately by a soil hydraulic model that is a closed-form equation with a certain number of paramParametric pedotransfer functions (PTFs), which predict parameeters, e.g., Brooks and Corey or van Genuchten equation. ters of a model from basic soil properties are useful in deriving continuous functions of soil properties, such as water retention curves. The A parametric approach is...

A laboratory investigation provided preliminary comparison of trace element contaminant water treatment capabilities for four iron-based filter materials. The iron-based filter materials tested were zero-valent iron (ZVI), porous iron composite (PIC), sulfur modified iron (SMI), and iron oxide/hydroxide (IOH). Two types of trace element contaminant solutions were tested, one combined As, Cr, an...

this study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ann) in broiler chicken. artificial neural networks (anns) are powerful tools for modeling systems in a wide range of applications. the ann model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...

one of the important aspects of soil is, knowing the relationships between spatial features of soil and quantity in statistical model. the goal of this research is to estimate saturated hydraulic conductivity by regression and co-active neuro-fuzzy inference system (anfis) with using the parameters of bulk density, real density, porosity, fractal dimension of particle size, and clay percent, si...

reinforced concrete (rc) slabs exhibit complexities in their structural behavior under load due to the composite nature of the material and the multitude and variety of factors that affect such behavior. current methods for determining the load-deflection behavior of reinforced concrete slabs are limited in scope and are mostly dependable on the results of experimental tests. in this study, an ...

The nonlinear solvers in numerical solution of water flow in variably saturated soils are prone to convergence difficulties. Many aspects can give rise to such difficulties, like very dry initial conditions, a steep pressure gradient and great variation of hydraulic conductivity occur across the wetting front during the infiltration of water.  So, the averaging method applied to compute hydraul...

background : the study examined the implementation of artificial neural network (ann) for the prediction of ammonia nitrogen removal from landfill leachate by ultrasonic process. methods : a three-layer backpropagation neural network was optimized to predict ammonia nitrogen removal from landfill leachate by ultrasonic process. considering the smallest mean square error (mse), the configuration...

The main purpose of the current research is comparing the results of Artificial Neural Network (ANN) with Adaptive Neuro-Fuzzy Inference System (ANFIS) with regard to determination of the importance of soil properties affecting clay dispersibility. After taking samples from two depths of 0-40 and 40-80 cm, the spontaneous and mechanical dispersions of clay were recorded using both weighing and ...

The examination of available vapor pressure data in the case of the methane, ethane, propane and butane halogenated refrigerants, allowed recommendations of standard equations for this property. In this study, three new models include a general correlation; a substance-dependent correlation and an artificial neural network (ANN) approach have been developed to estimate the saturated vapor press...