An Artificial Neural Network (ANN) was used to analyse the capillary rise in porous media. Wetting experiments were performed with fifteen liquids and fifteen different powders. The liquids covered a wide range  of  surface  tension ( 15.45-71.99  mJ/m2 )  and  viscosity (0.25-21 mPa.s). The powders also provided an acceptable range of particle size (0.012-45 μm) and surface free...

prediction of the heavy metals in the groundwater is important in developing any appropriate remediation strategy. this paper attempts to predict heavy metals (pb, zn and cu) in the groundwater from arak city, using artificial neural network (ann) algorithm by taking major elements (hco3, so4) in the groundwater from arak city. for this purpose, contamination sources in the groundwater were rec...

Although artificial neural networks can represent a variety of complex systems with a high degree of accuracy, these connectionist models are difficult to interpret. This significantly limits the applicability of neural networks in practice, especially where a premium is placed on the comprehensibility or reliability of systems. A novel artificial neural-network decision tree algorithm (ANN-DT)...

Economic Dispatch Problem (EDP) has been discussed with reference to the developments based on Artificial Neural Networks (ANN) approaches. A selected survey / overview on Economic Dispatch using Artificial Neural Network within the IEE/IEEE publications frame work have been presented.

Artificial intelligence is integral part of a neural network is based on mathematical equations and artificial neurons. The focus here is the implementation of the Artificial Neural Network Architecture (ANN) with on chip learning in analog VLSI for pattern recognition. It is a maximum likelohood classifier which can be implemented using VLSI. Modified Hamming neural network architecture is pre...

 ABSTRACT Background: A computer aided diagnosis system was established using the wavelet transform and neural network to differentiate malignant from benign in a   group of patients with histo-pathologically proved breast lesions based on the data derived independ­ently from time-intensity profile.   Materials and Methods: The per­formance of the artificial neural network (ANN) was evaluated u...

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well a...

This paper deals with artificial neural network (ANN) architecture, the multilayer Feed-forward (MLFF) network with back propagation learning. The training of an artificial neural network involves two passes. In the forward pass, the input signals propagate from the network input to the output. In the reverse pass the calculated error signals propagate backwards through the network where they a...

The tool wear is an unavoidable phenomenon when using coated carbide tools during hard turning of hardened steels. This   work focuses on the prediction of tool wear using regression analysis and artificial neural network (ANN).The work piece taken into consideration is AISI4140 steel hardened to 47 HRC. The models are developed from the results of experiments, which are carried out based on De...