This paper aims to describe and evaluate the proposed calibration model based on a neural network for post-processing of two essential meteorological parameters, namely near-surface air temperature (2 m) and 24 h accumulated precipitation. The main idea behind this work is to improve short-term (up to 3 days) forecasts delivered by a global numerical weather prediction (NWP) model called ECMWF (European Centre for Medium-Range Weather Forecasts). In comparison to the existing local weather models that typically provide weather forecasts for limited geographic areas (e.g., within one country but they are more accurate), ECMWF offers a prediction of the weather phenomena across the world. Another significant benefit of this global NWP model includes the fact, that by using it in several well-known online applications, forecasts are freely available while local models outputs are often paid. Our proposed ECMWF-enhancing model uses a combination of raw ECMWF data and additional input parameters we have identified as useful for ECMWF error estimation and its subsequent correction. The ground truth data used for the training phase of our model consists of real observations from weather stations located in 10 cities across two European countries. The results obtained from cross-validation indicate that our parametric model outperforms the accuracy of a standard ECMWF prediction and gets closer to the forecast precision of the local NWP models.

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.

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Airspace domain may be represented by a time-space consisting of a three-dimensional Cartesian coordinate system and time as the fourth dimension. A coordinate system provides a scheme for locating points given its coordinates and vice versa. The choice of coordinate system is important, as it transforms data to geometric representation. Visualization of the three and more dimensional data on the two-dimensional drawing - computer monitor is usually done by projection, which often can restrict the amount of information presented at a time. Using the parallel coordinate system is one of possibilities to present multidimensional data. The aim of this article is to describe basics of parallel coordinate system and to investigate lines and their characteristics in time-space.