An intelligent data analysis approach using self-organising-maps

A neural network-based data analysis model for the prediction and classification of field data has many attractions. However, there are problems in ensuring the generalisation capability of the data analysis model, in measuring the similarity between the original training data and the new unknown data and in processing large data volumes. This paper reports the use of self-organising maps (SOM) to overcome these difficulties and illustrates the utilisation of this approach though applications in the agricultural, resource exploration and mineral processing areas