Introduction: Artificial neural networks are a type of systems that use very complex technologies and non-algorithmic solutions for problem solving. These characteristics make them suitable for various medical applications. This study set out to investigate the application of artificial neural networks for differential diagnosis of thalassemia minor and iron-deficiency anemia. Methods: It is...

‎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...

Because of their parallelism, functional approXimation and learning capabilities, artificial neural networks can be effectively employed to apjmximate nonlinear functions, and to synthesize controllers for nonlinear dynamic systems. The use of dynamic neural networks to model and control dynamic systems is of great importance in the control paradigm. The intent of this paper is to use one such ...

The electric power industry is currently undergoing an unprecedented reform. One of the most exciting and potentially profitable recent developments is increasing usage of artificial intelligence techniques. The intention of this paper is to give an overview of using neural network (NN) techniques in power systems. According to the growth rate of NNs application in some power system subjects, t...

Leisure agriculture experiences continuous development. However, because most leisure farm areas are located in isolated or remote regions and the planning and construction of traffic networks is greatly restricted by terrain and geographical features, the roads in these areas are narrower than those in other regions. This study focuses on traffic flow forecasting using the advanced artificial ...

Memory plays a major role in Artificial Neural Networks. Without memory, Neural Network can not be learned itself. One of the primary concepts of memory in neural networks is Associative neural memories. A survey has been made on associative neural memories such as Simple associative memories (SAM), Dynamic associative memories (DAM), Bidirectional Associative memories (BAM), Hopfield memories,...

wood and non-wood resources in the forests have occupied a very important place in human’s life, since the advent of history. and today, developing technology along with increasing needs enhance the importance of the other functions of forests, in parallel with wood production. both in the world and as well in turkey, one of the featured functions of forests is the production of non-woodforest ...

to use soil hydrology processes (shp) models, which have increasingly extended during the last years, comprehensive knowledge about these models and their modeling approaches seems to be necessary. the modeling approaches can be categorized as either classical or non-classical. classical approaches mainly model the shp through solving the general unsaturated flow (richards) equation, numericall...

the static pull-in instability of beam-type micro-electromechanical systems is theoretically investigated. two engineering cases including cantilever and double cantilever micro-beam are considered. considering the mid-plane stretching as the source of the nonlinearity in the beam behavior, a nonlinear size-dependent euler-bernoulli beam model is used based on a modified couple stress theory, c...