normal 0 false false false en-us x-none ar-sa background: p revious studies confirmed that neural gene expression in embryonic stem cells (esc) could influence by chemical compounds through stimulating apoptotic pathway. we aimed to use escs-derived neural cells by embryoid body formation as an in vitro model for determination of neural gene expression changes in groups that treated by sera fro...

in this paper, a recurrent fuzzy-neural network (rfnn) controller with neural network identifier in direct control model is designed to control the speed and exhaust temperature of the gas turbine in a combined cycle power plant. since the turbine operation in combined cycle unit is considered, speed and exhaust temperature of the gas turbine should be simultaneously controlled by fuel command ...

Ranking of a company's financial information is one of the most important tools for identifying strengths and weaknesses and identifying opportunities and threats outside the company. In this study, it is attempted to examine the financial statements of companies to rank and explain the transparency of financial information of 198 companies during 2009-2017 using artificial intelligence and neu...

background: the current study investigated the possible role of the cell cycle regulator, cyclin-dependent kinases regulatory subunit-2; the angiogenic factor, plateletderived endothelial cell growth factor; and the cell adhesive molecule, neural cadherin, as prognostic factors in schistosomal and non-schistosomal-associated urothelial carcinomas. we also investigated the possible correlation b...

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...

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...

‎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...

the application of neural networks to model a laboratory scale inverse fluidized bed reactor has been studied. a radial basis function neural network has been successfully employed for the modeling of the inverse fluidized bed reactor. in the proposed model, the trained neural network represents the kinetics of biological decomposition of organic matters in the reactor. the neural network has b...