the main goal of this study was to investigate the way of affecting of water in production of cucumber. from aspect of econometrics, mutual relationships of production function and expenses have been analyzed in which translog cost function has been used. this function has been estimated using the conditional input demand functions, the shefard theorem, chemical fertilizer, animal fertilizer, l...

this paper studies an m/g/1 repairable queueing system with multiple vacations and n-policy, in which the service station is subject to occasional random breakdowns. when the service station breaks down, it is repaired by a repair facility. moreover, the repair facility may fail during the repair period of the service station. the failed repair facility resumes repair after completion of its re...

this paper intends to offer a new iterative method based on arti cial neural networks for finding solution of a fuzzy equations system. our proposed fuzzi ed neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. this architecture of arti cial neural networks, can get a real input vector and calculates its corresponding fu...

a new cost function based on stochastic fuzzy discrimination information measure is introduced in this paper. focusing on their significant parts, this cost function is used to find the optimal value of threshold for denoising image. it is, in fact, an extension of fuzzy entropy cost function by the present author. multivariable normal distribution is used for creating focus on significant part...

the purpose of this paper is to estimate the welfare cost of inflation in iran. we first use the long-horizon regression approach developed by fisher and seater (1993) to obtain an estimate of the inflation rate elasticity of money demand and then the baily’s consumer surplus approach to calculate the welfare cost function. the results show that reducing inflation rate from 40% to 0% increases ...

‎artificial neural networks have the advantages such as learning, ‎adaptation‎, ‎fault-tolerance‎, ‎parallelism and generalization‎. ‎this ‎paper is a scrutiny on the application of diverse learning methods‎ ‎in speed of convergence in neural networks‎. ‎for this aim‎, ‎first we ‎introduce a perceptron method based on artificial neural networks‎ ‎which has been applied for solving a non-singula...

artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. this paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. for this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. the sugg...