In this paper we address an artificial society in which action rules change with time. We propose a new method to design the action rules of agents in artificial society that can satisfy specified requests by using genetic algorithms (GAs). In the proposed method, each chromosome in the GA population represents a candidate set of action rules and the number of rule iterations. While the usual m...

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...

In this paper, the artificial boundary method for Poisson problem in an infinite domain with a concave angle is investigated. The exact and approximate elliptical arc artificial boundary conditions are given. The finite element approximation is formulated in a bounded domain using the approximate artificial boundary condition and error estimates are obtained. Finally, some numerical examples sh...

background: clinically frank thyroid nodules are common and believed to be present in 4% to 10% of the adult population in the united states. in the current literature, fine needle aspiration biopsies are considered to be the milestone of a model which helps the physician decide whether a certain thyroid nodule needs a surgical approach or not. a considerable fact is that sensitivity and specif...

the method of artificial neural network is used as a suitable tool for intelligent interpretation of gravity data in this paper. we have designed a hopfield neural network to estimate the gravity source depth. the designed network was tested by both synthetic and real data. as real data, this artificial neural network was used to estimate the depth of a qanat (an underground channel) located at...