Received Sep 17, 2017 Revised Nov 18, 2017 Accepted Nov 23, 2017 Computational time is high for Multilayer perceptron (MLP) trained with back propagation learning algorithm (BP) also the complexity of the network increases with the number of layers and number of nodes in layers. In contrast to MLP, functional link artificial neural network (FLANN) has less architectural complexity, easier to tr...

In this research, Artificial Neural Networks (ANNs) have been used as a powerful tool to solve the inverse kinematic equations of a parallel robot. For this purpose, we have developed the kinematic equations of a Tricept parallel kinematic mechanism with two rotational and one translational degrees of freedom (DoF). Using the analytical method, the inverse kinematic equations are solved for spe...

This paper discusses the use of neural networks in an underground radio-localization system. In a highly aggressive environment such as mines, reliability and robustness are essential to any operational system. Using UWB as the physical wireless propagation medium and combined with fingerprinting-geolocation and neural networks, this work tends to overcome many of the problems encountered in in...

Abstract. Artificial neural networks can be used to solve inverse problems. One relevant problem in hydrologic optics is the estimatation of the single scattering albedo from the emitted surface radiation. The multi-layer perceptron (MLP) can be applied to determine the albedo from the measured radiation. The MLP is designed with one hidden layer, where the activation employs the sigmoid functi...

The majority of today's Neural Networks are either Multi-Layer-Perceptron networks (MLP) or Feature-Maps like Kohonen's Self-Organizing Map (SOM). Usually they are simulated on ordinary single-processor von-Neumann hardware to be used for some kind of vector quantization, classiication or coding. However, these simulated Neural Networks are expensive in respect to the computational costs they d...

abstract erosion and sedimentation are the most complicated problems in hydrodynamic which are very important in water-related projects of arid and semi-arid basins. for this reason, the presence of suitable methods for good estimation of suspended sediment load of rivers is very valuable. solving hydrodynamic equations related to these phenomenons and access to a mathematical-conceptual model ...

Nowadays, computer scientists have shown the interest in the study of social insect’s behaviour in neural networks area for solving different combinatorial and statistical problems. Chief among these is the Artificial Bee Colony (ABC) algorithm. This paper investigates the use of ABC algorithm that simulates the intelligent foraging behaviour of a honey bee swarm. Multilayer Perceptron (MLP) tr...

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...

abstract infiltration is a significant process which controls the fate of water in the hydrologic cycle. the direct measurement of infiltration is time consuming, expensive and often impractical because of the large spatial and temporal variability. artificial neural networks (anns) are used as an indirect method to predict the hydrological processes. the objective of this study was to develop ...

In this paper, Rough Sets approach has been used to reduce the number of inputs for two neural networks-based applications that are, diagnosing plant diseases and intrusion detection. After the reduction process, and as a result of decreasing the complexity of the classifiers, the results obtained using Multi-Layer Perceptron (MLP) revealed a great deal of classification accuracy without affect...