APPLICATION OF ARTIFICIAL NEURAL NETWORKS TO COST FACTORS STIMULATING INNOVATION – THE CASE OF SLOVAKIA
APPLICATION OF ARTIFICIAL NEURAL NETWORKS TO COST FACTORS STIMULATING INNOVATION – THE CASE OF SLOVAKIA

Summary/Abstract: Artificial neural networks are means of processing complex data, and they use a number of interconnected processors and computational paths for their work. The architecture of the human brain inspires artificial neural networks, they are able to "learn" and analyse complex sets of data that would be difficult for simpler algorithms to handle. This work will show what a neural network is, its mathematical model, and how the neural network method is implemented in solving the interrelationships between inputs and outputs in the companies of the Central Europe. One hundred fifty-five small and medium-sized Slovak enterprises are the subject of modelling, where the inputs are the costs of training employees and the costs of science and research in the post-Soviet country. The output is the company's net turnover and it is analysed using the SPSS program. The first part is a description of neural networks; it explains what a neural network is and its classification. The second part of the methodology describes the methods used in the processing of the scientific article. It also mentioned the SPSS program, which was used on artificial neural networks. The following section presents the results of the analysis and the importance of the inputs are available. In the discussions section, the possibilities of further use of the given issue and finally the summary are discussed.

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