thermal conductivity is an important property of juices in the prediction of heat- and mass-transfer coefficients and in the design of heat- and mass-transfer equipment for the fruit juice industry. an artificial neural network (ann) was developed to predict thermal conductivity of pear juice. temperature and concentration were input variables. thermal conductivity of juices was outputs. the op...

The objective of this paper is to a design of pattern classification model based on the back-propagation (BP) algorithm for decision support system. Standard BP model has done full connection of each node in the layers from input to output layers. Therefore, it takes a lot of computing time and iteration computing for good performance and less accepted error rate when we are doing some pattern ...

introduction: a total dissolved solid (tds) is an important indicator for water quality assesment. since the composition of mineral salts and discharge affects the tds of water, it is important to understand the relationships of mineral salts composition with tds. materials and methods: in this study, methods of artificial neural networks with five different training algorithm,levenberg-marquar...

.......................................................................................................................................... 7 1 Introduction ............................................................................................................................... 8 2 – Laser Doppler Vibrometer Principle ...........................................................................

In this paper, we propose to study four meteorological and seasonal time series coupled with a multi-layer perceptron (MLP) modeling. We chose to combine two transfer functions for the nodes of the hidden layer, and to use a temporal indicator (time index as input) in order to take into account the seasonal aspect of the studied time series. The results of the prediction concern two years of me...

Bill Horne MakeWaves, Inc. 832 Valley Road Watchung, NJ 07060 We present a computationally efficient algorithm for function approximation with piecewise linear sigmoidal nodes. A one hidden layer network is constructed one node at a time using the method of fitting the residual. The task of fitting individual nodes is accomplished using a new algorithm that searchs for the best fit by solving a...

This paper investigates the construction of a wide class of singlehidden layer neural networks (SLNNs) with or without tunable parameters in the hidden nodes. It is a challenging problem if both the parameter training and determination of network size are considered simultaneously. Two alternative network construction methods are considered in this paper. Firstly, the discrete construction of S...

| First, an evolutionary algorithm for designing a single hidden layer feedfor-ward neural networks is proposed. The algorithm constructs a problem tailored neu-ral network by incremental introduction of new hidden units. Each new hidden unit is added to the network by linear partitioning of the hidden-layer representation through a genetic search. Second, a two stage algorithm speed-up is achi...