this study shows the usefulness of artificial neural network (ann) in maintenance planning and man-agement. an ann model based on the multi-layer perceptron having three hidden layers and four processing elements per layer was built to predict the expected downtime resulting from a breakdown or a maintenance activity. the model achieved an accuracy of over 70% in predicting the expected downtime.

Usually in multivariate regression problem it is assumed that residuals of outputs are independent of each other. In many applications a more realistic model would allow dependencies between the outputs. In this paper we show how a Bayesian treatment using Markov Chain Monte Carlo (MCMC) method can allow for a full covariance matrix with Multi Layer Perceptron (MLP) neural networks.

Neural networks have been widely used to solve complex realworld problems. Due to the complicate, nonlinear, non-convex nature of neural networks, formal safety guarantees for the behaviors of neural network systems will be crucial for their applications in safety-critical systems. In this paper, the reachable set estimation and verification problems for Nonlinear Autoregressive-Moving Average ...

Most of the real-world data samples used to train artificial neural networks (ANNs) consist of correlated information caused by overlapping input instances. Correlation in sampled data normally creates confusion over ANNs during the learning process and thus, degrades their generalization capability. This paper proposes the Principal Component Analysis (PCA) method for elimination of correlated...

Bionomic features of blowflies may be clarified and detailed by the deployment of appropriate modelling techniques such as artificial neural networks, which are mathematical tools widely applied to the resolution of complex biological problems. The principal aim of this work was to use three well-known neural networks, namely Multi-Layer Perceptron (MLP), Radial Basis Function (RBF), and Adapti...

This report examines the fault tolerance of multi-layer perceptron networks. First, the operation of a single perceptron unit is analysed, and it is found that they are highly fault tolerant. This suggests that neural networks composed from these units could in theory be extremely reliable. The multi-layer perceptron network was then examined, but surprisingly was found to be non-fault tolerant...

Evaporation process, the main component of the water cycle in nature, is essential in agricultural studies, hydrology and meteorology, the operation of reservoirs, irrigation and drainage systems, irrigation scheduling and management of water resources. Various methods have been presented for estimating evaporation from free surface including water budget method, evaporation from pan and experi...

The use of milk sample categorization for diagnosing mastitis using Kohonen’n Self-Organizing Feature Map (SOFM) is reported. Milk traits data of 14 weeks of milking from commercial dairy cows in New Zealand was used to train and test a SOFM network to discriminate the samples into its appropriate health category. The SOFM was useful in discriminating data patterns into four separate mastitis c...