In this paper, we present the mathematical foundations of a probabilistic neural network for gene selection and classification of high-dimensional microarray data. We present a catalogue of features that a classification system for microarray data should incorporate. We then use this catalogue and compare the theoretical properties of probabilistic neural networks with support vector machines w...

in this paper, the application of neural networks for simulation and optimization of the cogeneration systems has been presented. cgam problem, a benchmark in cogeneration systems, is chosen as a casestudy. thermodynamic model includes precise modeling of the whole plant. for simulation of the steadysate behavior, the static neural network is applied. then using dynamic neural network, plant is...

Through the development of artificial intelligence, some capabilities human beings have been replicated in computers. Among developed models, convolutional neural networks stand out considerably because they make it possible for systems to inherent humans, such as pattern recognition images and signals. However, conventional methods are based on deterministic which cannot express epistemic unce...

Perineuronal nets (PNNs) are unique extracellular matrix structures that wrap around certain neurons in the CNS during development and control plasticity in the adult CNS. They appear to contribute to a wide range of diseases/disorders of the brain, are involved in recovery from spinal cord injury, and are altered during aging, learning and memory, and after exposure to drugs of abuse. Here the...

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...

Computability of weightless neural networks is the major topic of this paper. In previous works it has been shown that, one can simulate a Turing machine with a weightless neural network (WNN) with an infinite tape. And it has also been shown that one can simulate probabilistic automata with a WNN with two queues. In this paper, we will show that is possible to simulate a probabilistic automata...