We have applied Bayesian regularisation methods to multi-layer perceptron (MLP) training in the context of a hybrid MLP– HMM (hidden Markov model) continuous speech recognition system. The Bayesian framework adopted here allows an objective setting of the regularisation parameters, according to the training data. Experiments were carried out on the ARPA Resource Management database.

Support vector regression (SVR) is a learning method based on the support vector machine (SVM) that can be used for curve fitting and function estimation. In this paper, the ability of the nu-SVR to predict the catalytic activity of the Fischer-Tropsch (FT) reaction is evaluated and the result is compared with two other prediction techniques including: multilayer perceptron (MLP) and subtractiv...

nowadays, software cost estimation (sce) with machine learning techniques are more performance than other traditional techniques which were based on algorithmic techniques. in this paper, we present a new hybrid model of multi-layer perceptron (mlp) artificial neural network (ann) and ant colony optimization (aco) algorithm for high accuracy in sce called multilayer perceptron ant colony optimi...

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...

This study uses a new data visualization method, developed by the first author, to investigate the reliability of a real world low-back-pain Multi-layer Perceptron (MLP) network from a hidden layer decision region perspective. Using decision region identification information from an explanation facility, the MLP training examples are discovered to occupy decision regions in contiguous class thr...

Soft Computing Techniques (SCT) are extensively used to estimate Labyrinth Weir's (LW) flow-rate. Due the multiplicity of these techniques, identifying most competent SCT is indispensable. This study aims flow-rate a sharp-crest triangular LW as function its side leg angle α and total head ratio (H/P) through several SCTs such Adaptive Neuro-Fuzzy Inference System (ANFIS), Multi-Layer Perceptro...

It is difficult to train a multi-layer perceptron (MLP) when there are only a few labeled samples available. However, by pretraining an MLP with vast amount of unlabeled samples available, we may achieve better generalization performance. Schulz et al. (2012) showed that it is possible to pretrain an MLP in a less greedy way by utilizing the two-layer contractive encodings, however, with a cost...

This paper presents a new approach for automatic image color correction, based on statistical learning. The method both parameterizes color independently of illumination and corrects color for changes of illumination. The motivation for using a learning approach is to deal with changes of lighting typical of indoor environments such as home and office. The method is based on learning color inva...

Feature projection by non-linear discriminant analysis (NLDA) can substantially increase classification performance. In automatic speech recognition (ASR) the projection provided by the pre-squashed outputs from a one hidden layer multi-layer perceptron (MLP) trained to recognise speech subunits (phonemes) has previously been shown to significantly increase ASR performance. An analogous approac...