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.

Since artificial neural networks (ANNs) can approximate any function, they have been applied in many fields including hydrology. In hydrology, there are important issues such as flood estimation and predicting rainfall-runoff in a certain area. In this presentation, we briefly introduce a popular feed-forward neural network model, so called “multi-layer perceptron (MLP)”, and review its applica...

Load forecasting has become one of the major areas of research in electrical engineering and is an important problem in operation and planning of electric power generation. Load forecasting is the technique for prediction of electrical load. STLF (Short term load forecast) is essential for Power system planning. In a deregulated market it is much need for a generating company to know about the ...

Heat transfer fluids have inherently low thermal conductivity that greatly limits the heat exchange efficiency. While the effectiveness of extending surfaces and redesigning heat exchange equipments to increase the heat transfer rate has reached a limit, many research activities have been carried out attempting to improve the thermal transport properties of the fluids by adding more thermally c...

Multilayer perceptrons with hard-limiting (signum) activation functions can form complex decision regions. It is well known that a three-layer perceptron (two hidden layers) can form arbitrary disjoint decision regions and a two-layer perceptron (one hidden layer) can form single convex decision regions. This paper further proves that single hidden layer feedforward neural networks (SLFN's) wit...

A globally convergent homotopy method is deened that is capable of sequentially producing large numbers of stationary points of the multi-layer perceptron mean-squared error surface. Using this algorithm large subsets of the stationary points of two test problems are found. It is shown empirically that the MLP neural network appears to have an extreme ratio of saddle points compared to local mi...

The research presented in this paper is based on the artificial neural networks recognition paradigm applied to Romanian isolated word recognition. The network, which is composed by three layer (a Multilayer Perceptron), is trained by conventional Back-propagation algorithm. The ANN speech recognition system based on Mel Frequency Cepstral Coefficients was developed using Matlab toolkit. The sy...