in the present study, five modeling approaches of ra, mlp, mnn, gff, and canfis were applied so as to estimate the radial overcut values in electrochemical drilling process. for these models, four input variables, namely electrolyte concentration, voltage, initial machining gap, and tool feed rate, were selected. the developed models were evaluated in terms of their prediction capability with m...

In this paper, imperialist competitive algorithm as a computational method is implemented in MATLAB software to estimate monthly average daily global solar radiation on horizontal surface for some different climate cities of Iran. The experimental coefficients for Angstrom model have been calculated using imperialist competitive algorithm for all different climate cities and output data compare...

In this paper, ensemble models are developed to accurately forecast software reliability. Various statistical (multiple linear regression and multivariate adaptive regression splines) and intelligent techniques (backpropagation trained neural network, dynamic evolving neuro–fuzzy inference system and TreeNet) constitute the ensembles presented. Three linear ensembles and one non-linear ensemble...

In the present study, five modeling approaches of RA, MLP, MNN, GFF, and CANFIS were applied so as to estimate the radial overcut values in electrochemical drilling process. For these models, four input variables, namely electrolyte concentration, voltage, initial machining gap, and tool feed rate, were selected. The developed models were evaluated in terms of their prediction capability with m...

difference aspects of multinomial statistical modelings and its classifications has been studied so far. in these type of problems y is the qualitative random variable with t possible states which are considered as classifications. the goal is prediction of y based on a random vector x ? ir^m. many methods for analyzing these problems were considered. one of the modern and general method of cla...

This paper is a survey on traditional linear regression techniques using the !I-, ez-, and &,-norm. We derive the characterization of the respective regression estimates (including optimality and uniqueness criteria), as well as discuss some of their statistical properties. @ 2002 Elsevier Science Ltd. All rights reserved. Keywords-el-, e2-, &-regression, Linear programming.