Abstract:The paper addresses the issue of management decision-making using artificial neural networks and their application in hotel management. Today, the development of tourism is of great importance and plays a very important role in the development of national economy. Balanced ranking and prediction model using financial and non-financial indicators with the application of artificial intelligence, allows us to reach a high level of effectivity and accuracy in evaluation of the financial and non-financial health of companies operating in this segment. This approach improves the manager's ability to understand complex contexts and make better decisions for further development. It also brings new managerial and scientific point of view of an in-depth analysis of the performance of these facilities. It can help the development of tourism in terms of the application of modern management techniques built on scientific principles and thereby better integrate science and practice.JEL Classification Numbers: C45, Z32; DOI: http://dx.doi.org/10.12955/cbup.v5.928Keywords: Prediction models, financial health, neural networks, management, tourism. IntroductionTourism development has great importance and plays a significant role in the development of national economies (Šenková and Šambronská, 2014; Council, 2016). Therefore, the efforts of each country are heading to assist in the development of this industry effectively. Management, economics and application of modern methods of economics and management have very important role in this development and thus equally important is managerial decision making. The ability to decide optimally is one of the most crucial parts of hotel manager's everyday job (O'Halloran, 2015). There are several methods that can be used in the field of managerial decision making. Many methods are based on an assessment of the performance of these businesses using the methods of financial analysis, prediction models, Economic Value Added or the methodology of the business performance analysis based on financial (Horváthová and Mokrišová, 2014) and non-financial indicators -Balanced Scorecard (Ivanickova et al., 2016). All these methods provide information to the optimal decision making by managers and to better controlling of these organizations. From modern economics models that can play a major role in the future, the management decision-making methods based on classification and prediction using artificial neural networks (ANN) are the most promising. Artificial neural networks are one of the modern trends in assessment of the financial and nonfinancial health of the business. They are particularly suitable when part of the decision-making processes depends on coincidence and/or deterministic dependency. They are therefore suitable for modeling and exploration of complex, single, often irreversible strategic management decisions (Hanne, 1997). During analytical phase of research, we have conducted many experiments with popular conventional models like Tafler model (Taffler and Tisshaw, 1977),...

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The concentration of copper and mercury in soils that are found at immission field of mining dumps, heaps and ponds, as the remains of mining-industry activity in Central Spiš region (Slovakia), were investigated. The concentration of copper and mercury in the soils were in the range of 35-1271 and 0.4-32.7 mg kg -1 , which exceeded the upper limits of potentially toxic elements concentration for agricultural soils of Slovakia (Act No. 220/2004 Coll.). The result from this study demonstrated that the soils in the region of Central Spiš had endured severe copper and mercury pollution. Subsequently, the laboratory tested the effect of a natural substance HUMAC Enviro on the reduction of copper and mercury in contaminated soils. The statistical analysis methods used in this study, namely Wilcoxon Matched Pairs Test, proved a statistically significant influence of the natural substance HUMAC Enviro on the reduction of copper content in an aqueous solution, in the case of mercury, the statistical significance was not proved. The application of natural substance HUMAC Enviro based on humic acids seems to be important in addressing current environmental problems related to environmental contamination