A novel technique is presented based on self-organizing neural networks for prediction of fertilizer distribution patterns of spreaders as a function of spreader settings and fertilizer properties. The main aim of the presented technique is to predict tendencies in the spreading distribution...

This paper presents an overview of an analysis method based on self-organizing maps (SOM) which was applied to an activated sludge treatment process in a pulp mill. The aim of the study was to determine whether the neural network modeling method could be a useful and time-saving way to analyze...

In this paper, we present multi-almost periodicity of a general class of discrete-time neural networks derived from a well-known semi-discretization technique, that is, coexistence and exponential stability of 2N almost periodic sequence solutions of discrete-time neural networks subjected to...

Morphological transformations are efficient methods for shape analysis and representation. In this paper two morphological shape descriptors are described for object feature representation. Neural networks are then employed for object recognition and classification. Various coding schemes and...

This paper illustrates how internal model control of nonlinear processes can be achieved by recurrent neural networks, e.g. fully connected Hopfield networks. It is shown that using results developed by Kambhampati et al. (1995), that once a recurrent network model of a nonlinear system has been...

Control of the precalcination degree in the precalciner of cement plants is a problem of great importance due to its effect to the quality of the clinker, the consumed energy and the byproducts of the whole cement pyroprocess. Divergence of the desired precalcination degree of the raw mix may...

Investigations were conducted to explore the feasibility of a prototype charge simulation retina machine vision system to identify shape and size, when different three-dimensional objects were arbitrarily located in the vision field of the retina. The system consisted of a light source, light...

The multi-criteria predictive control of nonlinear dynamical systems based on Artificial Neural Networks (ANNs) and genetic algorithms (GAs) are considered. The (ANNs) are used to determine process models at each operating level; the control action is provided by minimizing a set of control...

The development of the Financial Crisis throughout 2008 and 2009 has made many investors and fund managers question whether growth-based investment approaches have had their day. Value-based approaches built on fundamental analysis have resurfaced again. Typically, these value-based models use...

The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleksander and Stonham, 1979). They have some significant advantages over the more common and biologically plausible networks, such as multi-layer perceptrons; for example, n-tuple networks have been...