Discrete choice modeling is a fundamental part of travel demand forecasting. To date, this
field has been dominated by parametric approaches (eg, logit models), but non-parametric …

Predicting students' academic performance (SAP) provides invaluable information for
educational institutes' authorities. This information offers numerous opportunities for …

The paper presents a Neural Network model for modeling academic profile of students. The
proposed model allows prediction of students' academic performance based on some of …

Educational data mining provides the process of applying different data mining tools and
techniques to analyze and visualize the data of an institution and can be used to discover a …

The probabilistic neural network (PNN) is a special type of radial basis neural network used
mainly for classification problems. Due to the size of the network after training, this type of …

Offshore structures are subjected to wave, wind, and earthquake loads. The failure of
offshore structures can cause sea pollution as well as loss of property and life. Therefore, the …

In this paper, we propose three neural networks based methods for fault detection and
isolation of asynchronous machine: a probabilistic neural network (PNN), multi-layer …

This paper presents the Support Vector Regression (SVR) to predict the stability number of
armor blocks of breakwaters. The experimental data of van der Meer are used as the training …

In this work, a new training algorithm for probabilistic neural networks (PNN) is presented.
The proposed algorithm addresses one of the major drawbacks of probabilistic neural …

For human interactive communication facial emotion plays a key role and is often seen in
many actual applications. In recent times, the detection of facial expression from frontal still …