In this paper, we study linear fuzzy time-variant optimal control systems using the generalized differentiability concept and we present the general form of optimal controls and states. Some examples are provided to illustrate our results.

We present a novel and flexible approach to the problem of feature selection, called grafting. Rather than considering feature selection as separate from learning, grafting treats the selection of suitable features as an integral part of learning a predictor in a regularized learning framework. To make this regularized learning process sufficiently fast for large scale problems, grafting operat...

Performance on symbolic and non-symbolic numeric order determination tasks was examined as predictors of Woodcock Johnson calculation (exact) and computation estimation (approximate) scores among university aged adults. For Woodcock Johnson scores, only the symbolic task variant was found to be a significant predictor of performance outcomes after entering both task variants into a multiple reg...

this paper estimates the determinants of inflation in iran using a linear and non- linear regression model over the period 1959-2008. in the model specification, the conventional variables (liquidity, production and exchange rate) as well as positive and negative oil revenue shocks, monetary disequilibrium, and demand gap are considered. the results show that nonlinear time series regression mo...

in this work, removal of c. i. acid red 14 was investigated by pumice stone as a low cost adsorbent. various parameters such as initial dye solution, contact time and ph were studied. removal of dye were increased by increasing of contact time and initial dye solution and deceased by increasing of ph. three isotherm models were studied. linear and non-linear regression analyses were used for de...

This Ph.D. thesis is devoted to algorithms for two optimization problems, and their implementation. The algorithms are based on solving linear M-estimation problems. First, an algorithm for the non-linear M-estimation problem is considered. The main idea of the algorithm is to linearize the residual function in each iteration and thus calculate the iteration step by solving a linear M-estimatio...