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The approach of InterCriteria Analysis (ICA) was applied for the aim of reducing the set of variables on the input of a neural network, taking into account the fact that their large number increases the number of neurons in the network, thus making them unusable for hardware implementation. Here, for the first time, with the help of the ICA method, correlations between triples of the input parameters for training of the neural networks were obtained. In this case, we use the approach of ICA for data preprocessing, which may yield reduction of the total time for training the neural networks, hence, the time for the network's processing of data and images.

In a series of papers, the initiation and development of forest fires are described in terms of the cellular automata-based Game Method for Modelling (GMM), modelling a particular area as an orthogonal grid of square cells whose values are changing with respect to predefined rules. In the present leg of this research, the simulation of the wildfire that occurred in the Kresna Gorge in Bulgaria in August 2017 is presented, rendering an account of the wind, characterized by its direction and intensity, and evaluating the impact of the fire iteratively in terms of temporal intuitionistic fuzzy sets that maintain the information about the degrees of burnt and unaffected areas. The results from the software product FireGrid, implementing the GMM-model developed by the authors, are also compared to the results from the software application FlamMap. Additionally, the paper presents for the first time the basic properties of the defined operations and operators over temporal intuitionistic fuzzy pairs.

The artificial neural networks (ANN) are a tool that can be used for object recognition and identification. However, there are certain limits when we may use ANN, and the number of the neurons is one of the major parameters during the implementation of the ANN. On the other hand, the bigger number of neurons slows down the learning process. In our paper, we propose a method for removing the number of the neurons without reducing the error between the target value and the real value obtained on the output of the ANN's exit. The method uses the recently proposed approach of InterCriteria Analysis, based on index matrices and intuitionistic fuzzy sets, which aims to detect possible correlations between pairs of criteria.