In the Artificial Intelligence field, two areas have attracted a lot of attention in the past years: Artificial Neural Networks (ANN’s) and Genetic Algorithms (GA). The artificial neural networks, by their capacity to learn non-linear relationships between an input and an output space have a lot of applications: modeling and controlling dynamic processes and systems, signal processing, pattern ...

in recent years, researches on reinforcement learning (rl) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. neural network reinforcement learning (nnrl) is among the most popular algorithms in the rl framework. the advantage of using neural networks enables the rl to search for optimal policies more efficiently in several real-life applicat...

in this study, using sound created by wheat grain passing through a pipe, wheat flow rate was measured. the developed device consists of a hopper, metering device, sound sensor, delivery tube, dc motor and power supply. several wheat mass flow rates were tested and the sound signal created by the passage of the grain through the discharge tube was measured and transferred to a computer using da...

This tutorial article deals with the basics of artificial neural networks (ANN) and their applications in pattern recognition. ANN can be viewed as computing models inspired by the structure and function of the biological neural network. These models are expected to deal with problem solving in a manner different from conventional computing. A distinction is made between pattern and data to emp...

ii I do not know what I may appear to the world, but to myself I seem to have been only like a boy playing on the seashore, and diverting myself in now and then finding a smoother pebble, or a prettier shell than ordinary whilst the great ocean of truth lay all undiscovered before me. ABSTRACT iii ABSTRACT During a number of years the two fields of artificial neural networks (ANNs) and highly p...

the ability of artificial neural network (ann) for estimating the natural gas demand load for the next day and month of the populated cities has shown to be a real  concern. as the most applicable network, the ann with multi-layer back propagation perceptrons is used to approximate functions. throughout the current work, the daily effective temperature is determined, and then the weather data w...

in recent years, artificial neural networks (anns) have been widely used for flood esti-mation. in this study, an ann model based on the geomorphologic characteristics of a watershed such as the number of possible paths and their probabilities is developed (gann model). nodes in the input layer are allocated to the surface flows, subsurface flows, excess-rainfall and infiltrated rain. the numbe...

For the past several years, Cyprus has been facing an unprecedented water crisis. Four options that have been considered to help resolve the problem of drought in Cyprus include imposing effective water use restrictions, implementing water-demand reduction programs, optimizing water supply systems, and developing sustainable alternative water source strategies. An important aspect of these init...

in this article different types of artificial neural networks (ann) were used for cntfet (carbon nanotube transistors) simulation. cntfet is one of the most likely alternatives to silicon transistors due to its excellent electronic properties. in determining the accurate output drain current of cntfet, time lapsed and accuracy of different simulation methods were compared. the training data for...

Artificial Neural Network is widely used to learn data from systems for different types of applications. The capability of different types of Integrated Circuit (IC) based ANN structures also depends on the hardware backbone used for their implementation. In this work, Field Programmable Gate Array (FPGA) based Multilayer Perceptron Artificial Neural Network (MLP-ANN) neuron is developed. Exper...