The aim of this paper is to propose an interdisciplinary evolutionary connectionism approach for the study of the evolution of modularity. It is argued that neural networks as a model of the nervous system and genetic algorithms as simulative models of biological evolution would allow us to formulate a clear and operative definition of module and to simulate the different evolutionary scenarios...

quantitative relationships between structures of twenty six of 2-mercaptoimidazoles as c-c chemokine receptor type 2 (ccr2) inhibitors were assessed. modeling of the biological activities of compounds of interest as a function of molecular structures was established by means of genetic algorithm multivariate linear regression (ga-mlr) and genetic algorithm (ga-ann). the results showed that, the...

A molecular model for the morphogenesis of the central nervous system is built and solved by computer. The formalism rests on molecular-biological data gathered from insects and vertebrates during neural differentiation and neuronal fate specification. Two genetic, hierarchically organized switches are introduced, one associated with f1p4al tissue formation, and the other with neuronal specific...

Apparent shear stress acting on a vertical interface between the main channel and floodplain in a compound channel serves to quantify the momentum transfer between sub sections of this cross section. In this study, three soft computing methods are used to simulate apparent shear stress in prismatic compound channels. The Genetic Algorithm Artificial neural network (GAA), Genetic Programming (GP...

In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...

In this paper we present a recurrent neural network model to recognize efficient Decision Making Units(DMUs) in Data Envelopment Analysis(DEA). The proposed neural network model is derived from an unconstrained minimization problem. In theoretical aspect, it is shown that the proposed neural network is stable in the sense of lyapunov and globally convergent. The proposed model has a single-laye...

The incremental sheet metal forming (ISMF) process is a new and flexible method that is well suited for small batch production or prototyping. This paper studies the use of the finite element method in the incremental forming process of AA1050 sheets to investigate the influence of tool diameter, vertical step size, and friction coefficient on forming force, spring-back, and thickness distribut...

introduction: with using multiple linear regression (mlr), can simultaneously analyses several different variables, but to get the desirable results from the mlr, the samples must be much and accurate. therefore, this method has high sensitivity and may cause errors in results. in addition, to use this method, the variable must have normal distribution and modification follow from a linear rela...