Comparative Study of the Identification Methods of the Management System of the Day-Ahead Market of Polish Energy Market S.A.

Nowadays, identification and neural methods are used more and more often in modeling IT forecasting systems in addition to analytical methods. Six characteristic models used to forecast the Day-Ahead Market system functioning as a transaction management system at the Polish Power Exchange (POLPX) and the Nord Pool Spot market have been selected for comparative analysis. The research was preceded by a detailed discussion of modern criteria used to assess the quality of model fitting to the system, namely: effectiveness, efficiency, and robustness. In the literature, there are two main groups of system modeling methods, namely time series modeling methods and identification modeling methods, including neural modeling methods. Modeling usually results in such models as parametric models and artificial neural networks learned neural models of the Day-Ahead Market, as well as time series models, among others. In the comparative analysis, special attention was paid to the accuracy of the obtained models concerning the system. It has been pointed out that the studied solutions used to measure the accuracy of modeling criteria such as accuracy of fit or efficiency, and did not use the modeling efficiency, which is very important in IT forecasting systems for such large markets as the Day-Ahead Market of POLPX. The search for the best market models, including identification models of the Day-Ahead Market operation that can be used in electricity price forecasting is a very important issue both from the point of view of algorithmic solutions and economical solutions.

Unbounded Model Checking for ATL

In this paper, we deal with verification of multi-agent systems represented as concurrent game structures. To express properties to be verified, we use Alternating-Time Temporal Logic (ATL) formulas. We provide an implementation of symbolic model checking for ATL and preliminary, but encouraging experimental results.

Firefly algorithm applied to the job-shop scheduling problem

The job shop scheduling problem (JSSP) is one of the most researched scheduling problems. This problem belongs to the NP-hard class. An optimal solution for this category of problems is rarely possible. We try to find suboptimal solutions using heuristics or metaheuristics. The firefly algorithm is a great example of a metaheuristic. In this paper, this algorithm is used to solve JSSP. We used some benchmarking JSSP datasets for experiments. The experimental program was implemented in the aitoa library. We investigated the optimal parameter settings of this algorithm in terms of JSSP. Analysis of the experimental results shows that the algorithm is useful to solve scheduling problems.

Neural model of human gait and its implementation in MATLAB and Simulink Environment using Deep Learning Toolbox

The article presents selected results of research on the modeling of humanoid robots, including the results of neural modeling of human gait and its implementation in the environment MATLAB and Simulink with the use of Deep Learning Toolbox. The subject of the research was placed within the scope of the available literature on the subject. Then, appropriate research experiments on human movement along a given trajectory were developed. First, the method of measuring the parameters present in the experiment was established, i.e. input quantities (displacement of the left heel, displacement of the right heel) and output quantities (displacement of the measurement point of the human body in space). Then, research experiments were carried out, as a result of which numerical data were measured in order to use them for teaching and testing the Artificial Neural Network. The Perceptron Artificial Neural Network architecture was used to build a model of a neural human walk along a given trajectory. The obtained results were discussed and interpreted, drawing a number of important conclusions.

ICT security in tax administration - AV protection systems

The article discusses the topic of ICT security in tax administration. This paper presents a study of the security level of endpoints8, servers using three antivirus protection systems. It discusses three independent solutions used to ensure the protection of ICT equipment in public administration.

Quantum inspiration to build a neural model based on the Day-Ahead Market of the Polish Power Exchange

The article is an attempt of the methodological approach to the proposed quantum-inspired method of neural modeling of prices quoted on the Day-Ahead Market operating at TGE S.A. In the proposed quantum-inspired neural model it was assumed, inter alia, that it is composed of 12 parallel Perceptron ANNs with one hidden layer. Moreover, it was assumed that weights and biases as processing elements are described by density matrices, and the values flowing through the Artificial Neural Network of Signals are represented by qubits. Calculations checking the correctness of the adopted method and model were carried out with the use of linear algebra and vector-matrix calculus in MATLAB and Simulink environments. The obtained research results were compared to the results obtained from the neural model with the use of a comparative model.

Neural modelling of electricity prices quoted on the Day-Ahead Market of TGE S.A. shaped by environmental and economic factors

The paper contains the results of research on the impact of the number of factors used to build the Day-Ahead Market model at Polish Power Exchange S.A. Five models with a different number of factors influencing the model were tested. To test the quality of models according to the adopted evaluation criteria, i.e., mean square error and the coefficient of determination for the weighted average prices sold in a given hour of the day, the influence of weather factors, socio-economic factors and energy demand were adopted. The results obtained from the analysis show a relatively high correctness of the simplest of the adopted models, which differs slightly from the best model.

Supporting Process of Independent Navigation Inside Buildings Based on Low-Energy Bluetooth Transmitters

Thanks to the use of satellite positioning systems (including GPS) the ability to determine a user's position in open spaces has become a necessary element of everyday life. Nowadays people cannot imagine moving in an "urban jungle” with paper maps without electronic support, but dozens of years ago those maps were more popular than satellite navigation. A similar revolution may also await navigations in closed spaces such as public or commercial buildings. Because as the urbanisation process, the surfaces of various buildings grow, which significantly impedes orientation in them, especially for the blind or visually impaired users. As satellite navigation systems are burdened with errors, which increase when trying to use them in confined spaces, it becomes necessary to use more accurate technology. As a step towards solving this problem, we propose a solution supporting the navigation of users, especially the visually impaired, inside buildings. Our approach is based on using low energy Bluetooth transmitters and a method of determining the user's position using the trilateration algorithm and the appropriate placement of transmitters in a space.

Technologies supporting independent moving inside buildings for people with visual impairment

Sustainable Development Goals (SDGs) include disability and persons with disabilities for example partially sighted or blind. Disability is referenced in multiple parts of the SDGs, specifically in the parts related to education, growth and employment, inequality, accessibility of human settlements and buildings. The paper presents selected technologies that support independent movement blind people inside huge buildings. The paper will refer to two SDGs: No 9 and No 11. There needs to be a future in which cities provide opportunities for all with access to basic services, housing, friendly public buildings, transportation and more, even to people with eye disabilities. This paper presents selected systems for finding objects or places, recognizing objects inside rooms and navigation inside buildings based on nonradio and wireless technologies. The following technologies and solutions were presented and compared: physical items, smartphone cameras, laser rangefinders, pedestrian dead-reckoning, intelligent lighting, Wi-Fi, BLE beacons, magnetic fields and barometric pressure sensors.

Human integration in an ontology-based IoT system

The IoT systems are growing field of automation. In contrast to industrial applications, where the system is custom made for each customer or use case, the home IoT systems can be composed and used in many, sometimes dangerous and unpredictable, ways. This paper presents a system that is based on a common ontology as a unified and universal method of representing the environment including humans. Such approach allows for easy integration of heterogenous devices and declarative definition of services, tasks, and rules ensuring human safety and/or comfort.