The utilization of energy is on the rise in current trends due to increasing consumptions by households. Smart buildings, on the other hand, aim to optimize energy, and hence, the aim of the study is to forecast the cost of energy consumption in smart buildings by effectively addressing the minimal energy consumption. However, smart buildings are restricted, with limited power access and capacity associated with Heating, Ventilation and Air Conditioning (HVAC) units. It further suffers from low communication capability due to device limitations. In this paper, a balanced deep learning architecture is used to offer solutions to address these constraints. The deep learning algorithm considers three constraints, such as a multi-objective optimization problem and a fitness function, to resolve the price management problem and high-level energy consumption in HVAC systems. The study analyzes and optimizes the consumption of power in smart buildings by the HVAC systems in terms of power loss, price management and reactive power. Experiments are conducted over various scenarios to check the integrity of the system over various smart buildings and in high-rise buildings. The results are compared in terms of various HVAC devices on various metrics and communication protocols, where the proposed system is considered more effective than other methods. The results of the Li-Fi communication protocols show improved results compared to the other communication protocols.
The principal goal of this study is to provide economic analysis of value added in the context of problems of competitive position in enterprises. A relationship presented in the literature that occurs between competitive position in the enterprise and its ability to generate value added. The selected tools for measurement of competitive position in the enterprise were presented, among which the authors included enterprise concentration rate and economic value added. EVA concept was also characterized. The empirical investigations focused on the companies listed in the Warsaw Stock Exchange. Based on the empirical analysis, the study found a significant difference between the place in the ranking of the value added and the degree of enterprise's participation in the market.
The primary focus of this study is on theoretical and empirical analysis of selected directions of innovative activities carried out in enterprises. The significance of these problems is connected with the role performed by innovations in improving and maintaining competitiveness in enterprises. The investigations presented in the study focused on the importance and manifestations of innovativeness of enterprises as well as highlighting contemporary characteristics of innovations. The empirical part of the study analyzed innovative activity of enterprises based on such criteria as level of outlays on innovations incurred by the enterprise, equipping the enterprise in means of production processes automation as well as the level of technology transfer and using the technology. The empirical examinations were carried out based on the data contained in the Statistical Yearbooks published by the Central Statistical Office for the years 2008-2012.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.