pervious concrete is a concrete mixture prepared from cement, aggregates, water, little or no fines, and in some cases admixtures. the hydrological property of pervious concrete is the primary reason for its reappearance in construction. much research has been conducted on plain concrete, but little attention has been paid to porous concrete, particularly to the analytical prediction modeling o...

traditional poultry production has changed to a considerable industry after few decades. now, poultry industry is one of the main sectors to obtain the required protein for human consumption. prediction of the weight and number of eggs according to economic traits can improve the efficiency of production and the profit of producers. in present study, the weight and number of eggs in mazandaran ...

this paper presents a hybrid approach to developing a short-term traffic flow prediction model. in thisapproach a primary model is synthesized based on neural networks and then the model structure is optimized throughgenetic algorithm. the proposed approach is applied to a rural highway, ghazvin-rasht road in iran. the obtainedresults are acceptable and indicate that the proposed approach can i...

this paper aims to evaluate the impact of several indices of market structure including entry to barrier, economies of scale and concentration degree on 140 active industries using the digit. accordingly, we apply three methods including cost disadvantages ratio ( ), herfindahl–hirschman concentration index ( ) and comanor and willson criterion in order to assess the economies of scale and usin...

in this work, artificial neural network (ann) has been employed to propose a practical model forpredicting the surface tension of multi-component mixtures. in order to develop a reliable modelbased on the ann, a comprehensive experimental data set including 15 ternary liquid mixtures atdifferent temperatures was employed. these systems consist of 777 data points generally containinghydrocarbon ...

numerous studies yet have been carried out on downscaling of the large-scale climate data usingboth dynamical and statistical methods to investigate the hydrological and meteorological impacts of climatechange on different parts of the world. this study was also conducted to investigate the capability of feedforwardneural network with error back-propagation algorithm to downscale the provincial...

objective(s): this study aims to evaluate and predict the thermal conductivity of iron oxide nanofluid at different temperatures and volume fractions by artificial neural network (ann) and correlation using experimental data. methods: two-layer perceptron feedforward artificial neural network and backpropagation levenberg-marquardt (bp-lm) training algorithm are used to predict the thermal cond...

a sigmoid function is necessary for creation a chaotic neural network (cnn). in this paper, a new function for cnn is proposed that it can increase the speed of convergence. in the proposed method, we use a novel signal for controlling chaos. both the theory analysis and computer simulation results show that the performance of cnn can be improved remarkably by using our method. by means of this...