Prediction of electricity energy consumption plays a crucial role in the electric power industry. Accurate forecasting is essential for electricity supply policies. A characteristic feature of electrical energy is the need to ensure a constant balance between consumption and electricity production, whereas electricity cannot be stored in significant quantities, nor is it easy to transport. Electricity consumption generally has a stochastic behavior that makes it hard to predict. The main goal of this study is to propose the forecasting models to predict the maximum hourly electricity consumption per day that is more accurate than the official load prediction of the Slovak Distribution Company. Different models are proposed and compared. The first model group is based on the transverse set of Grey models and Nonlinear Grey Bernoulli models and the second approach is based on a multi-layer feed-forward back-propagation network. Moreover, a new potential hybrid model combining these different approaches is used to forecast the maximum hourly electricity consumption per day. Various performance metrics are adopted to evaluate the performance and effectiveness of models. All the proposed models achieved more accurate predictions than the official load prediction, while the hybrid model offered the best results according to performance metrics and supported the legitimacy of this research.

The development of an economy and, in particular, the construction of new infrastructure as well as industrial enterprises creates demand for the road transport of oversized freight that exceeds the maximum permissible total mass of vehicle combinations with its share on the axles. Failure to comply with the defined technological processes and a deficiency in the assessment of permitting such forms of transportation can have a large adverse effect, predominantly on the lifetime of bridges in a road network, which can have international implications as well. There is no legislation adopted by the EU Member States, which would at least partially unify the authorisation procedures of these forms of transportation and, therefore, it results in problems when crossing borders and leads to differences related to the assessment of bridge passages. If there is no systematic inspection of this kind of transportation, it can lead to permanent damage of these bridges as well. Currently, and not only in Slovakia but also in other states, the assessment of bridge passage for certain routes is used for heavy and oversized transportation. It means that if we use 100 transports, 100 assessments of individual routes are needed, although some are the same routes or the same vehicles/vehicle combinations used for a number of transports. Thus, the authors designed a global assessment for bridge passage in relation to heavy and oversized road transport while verifying it in the conditions of the EU Member State from Central Europe–Slovakia. Roads are full of different types of vehicles/vehicle combinations for which the axle loads and distances of the axles (wheelbases) are important. Thus, there were vehicle/vehicle combinations parameters (big data) observed, for which the routes relating to heavy and/or oversized transportation were assessed from 1 January 2016 to 31 December 2020 in Slovakia. The global assessment of bridge passage introduces an entirely new approach within the procedure for obtaining a special permission for road use as well as within transport use itself. Given the low presence of freight with an abnormal axle load or enormous total mass, it is appropriate to define the limited conditions under which it would be possible to implement the global assessment in practice as well.

Car drivers have been suffering from road bottlenecks due to the constant increase in the number of vehicles that are not matched by the growth of the road network. Obstacles on a road or a road narrowed to one bidirectional are an accompanying phenomenon of a congested transport network. This paper solves a queueing system generated by such a road bottleneck managed by traffic lights. Generally, the problem can be classified as a Semi-Markov process with stochastic arrivals and deterministic service with a queue of an appropriate length. In order, to allow for an analytical solution, a simplifying assumption that the incoming flow of cars has a uniform distribution is made. A complex analysis of possible scenarios is done, the efficiency and the average waiting times are calculated. The results confirm the nature of the studied system and allow an optimization of the system settings.

The demand for public transport by tourists increases significantly in tourist-attractive destinations. This is in addition to regular passengers commuting to school and work. The level of irregular demand is influenced by several factors related to the characteristics of the day of the week, the period of the year, and the current weather. The main goal of the paper is to verify which factors most influence the irregular demand for transport in a tourist-attractive area to ensure operational planning of public passenger transport. Thanks to this, it is possible to ensure sufficient capacity and, at the same time, the efficiency of the operation of public passenger transport. The paper analyzes the main determinants of the irregular demand for regional public rail passenger transport in the High Tatras region of Slovakia. Multiple linear regressions were used to model the number of irregular passengers. The variables representing the day of the week, the attractiveness of the period, and the holiday were found to be the most significant. The variables describing the weather such as maximum daily temperature, precipitation, clouds, and wind had less influence. The obtained mathematical models for forecasting the irregular demand for public passenger transport can help optimize the timetable’s operational setting and the train sets’ size.