This paper presents the performance comparison of two architectures of neural networks: multi-layer perceptron (MLP) neural networks and radial basis function (RBF) neural networks on face recognition system (FRS). We are training MLP using different variants of back-propagation (BP) algorithm. AT&T database has been used for performance comparison. The BP is gradient descent based iterative al...

Prediction of Atmospheric Pressure is one important and challenging task that needs lot of attention and study for analyzing atmospheric conditions. Advent of digital computers and development of data driven artificial intelligence approaches like Artificial Neural Networks (ANN) have helped in numerical prediction of pressure. However, very few works have been done till now in this area. The p...

in this paper, a state-of-the-art neuron mathematical model of neural tensor network (ntn) is proposed to rdf knowledge base completion problem. one of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. for this reason, a new representation of this network is suggested that solves this difficulty. in the representation, th...

One of the most severe problems in power plants, petroleum and petrochemical industries is accurate determination phase fractions two-phase flows. In this paper, we carried out experimental investigations to validate simulations for water–air, flow an annular pattern. To end, performed finite element with COMSOL Multiphysics, conducted concave electrode shape and, finally, compared both results...

In this paper, a state-of-the-art neuron mathematical model of neural tensor network (NTN) is proposed to RDF knowledge base completion problem. One of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. For this reason, a new representation of this network is suggested that solves this difficulty. In the representation, th...

A novel neural-network based technique is described for the remote condition-monitoring of an in-service gas-turbine flowmeter. The method uses a C language implementation of a modified multi-layer perceptron (MLP) neural networks, which enables detection of the accumulation of contaminating material on the rotor blades that could lead to changes in meter-factor and loss of calibration.

background: municipal solid waste (msw) is the natural result of human activities. msw generation modeling is of prime im­portance in designing and programming municipal solid waste management system. this study tests the short-term pre­diction of waste generation by artificial neural network (ann) and principal component-regression analysis. methods: two forecasting techniques are presented in...

the use of neural networks methodology is not as common in the investigation and pre-diction noise as statistical analysis. the application of artificial neural networks for pre-diction of power tiller noise is set out in the present paper. the sound pressure signals for noise analysis were obtained in a field experiment using a 13-hp power tiller. during measurement and recording of the sound ...

Using ANN algorithms to address optimization problems has substantially benefited recent research. This study assessed the heating load (HL) of residential buildings’ heating, ventilating, and air conditioning (HVAC) systems. Multi-layer perceptron (MLP) neural network is utilized in association with MVO (multi-verse optimizer), VSA (vortex search algorithm), SOSA (self-organizing self-adaptive...

Abstract—Human beings have the ability to make logical decisions. Although human decision making is often optimal, it is insufficient when huge amount of data is to be classified. Medical dataset is a vital ingredient used in predicting patient’s health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance ...