We present an estimate approach to compute the viscoplastic behavior of a polymer matrix composite (PMC) under different thermomechanical environments. This investigation incorporates computational neural network as the tool for deter-mining the creep behavior of the composite. We propose a new second-order learning algorithm for training the multilayer networks. Training in the neural network ...

This paper refines the analysis of cotraining, defines and evaluates a new co-training algorithm that has theoretical justification, gives a theoretical justification for the Yarowsky algorithm, and shows that co-training and the Yarowsky algorithm are based on different independence assumptions.

This paper explores collaborative ability of co-training algorithm. We propose a new measurement (CA) for representing the collaborative ability of co-training classifiers based on the overlapping proportion between certain and uncertain instances. The CA measurement indicates whether two classifiers can co-train effectively. We make theoretical analysis for CA values in co-training with indepe...

in this study a machine learning algorithm was applied in order to develop a predictive model for the changes in phytoplankton biomass (chlorophyll a) in the lower nakdong river, south korea. we used a “hybrid evolutionary algorithm (hea)” which generated model consists of three functions ‘if-thenelse’ on the basis of a 15-year, weekly monitored ecological database. we used the average ...

abstract: this paper represents a novel use of artificial neural networks in medical science. the proposed technique involves training a multi layer perceptron (mlp) (a kind of artificial neural network) with a bp learning algorithm to recognize a pattern for the diagnosing and prediction of five blood disorders, through the results of blood tests from h1 machine. the blood test parameters and ...

abstract: in this paper, a method for determination of refractive index in membrane of fuel cell on basis of three-longitudinal-mode laser heterodyne interferometer is presented. the optical path difference between the target and reference paths is fixed and phase shift is then calculated in terms of refractive index shift. the measurement accuracy of this system is limited by nonlinearity erro...

today, with the advanced statistical techniques and neural networks, predictive models of distribution have been rapidly developed in ecology. purpose of this research is to predict and map the distribution of tetranychus urticae koch (acari: tetranychidae) using mlp neural networks combined with genetic algorithm in surface of farm. population data of pest was obtained in 2016 by sampling in 1...