Abstract:The aim of this research is to develop a methodology for calculating the standard time using neural networks. The paper presents research questions and proposes a methodology. In addition, the methods used to calculate the standard time in the Czech Republic and in other parts of the world are presented, and the basics of the mathematics of neural networks are shortly explained. The paper also provides an example that represents a simple application of a neural network. This example is designed to confirm some assumptions and to arrive at the basic conclusions regarding the operation of models created using neural networks.

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Purpose Each production process in construction is closely connected with the question of costs and deadlines. In every project an investor or customer, as well as the construction company, has to meet the planned completion date and the estimated costs associated with the construction. In practice, determining the duration of construction at minimum costs is still not based on the reliable calculation, and in the planning of costs, the connection between terms and financial costs is rarely taken into account. Method The queues theory examines systems with operating channels, where the process of queues formation takes place and subsequent servicing of the customers by servicing centers. The main objective of the queues theory is to determine the laws under which the system works, and further to create the most accurate mathematical model that takes into account various stochastic influences on the process. The entire construction process can be examined from the point of view of a customer who is waiting in the queue and is interested primarily in the waiting time, as well as from the point of view of servicing centers. A waiting element decides if you join the queue, or to go to another system entirely. In terms of servicing centers, the priority is to determine the occupancy of the channel and the probability of failure, including the time of repair. A servicing center should also reliably identify the time per customer service, taking into account the current construction task. Results & Discussion The present study demonstrates that it is possible to simulate the complex process of construction, containing hundreds of individual construction processes, mathematically and technically, with a number of simplifications, and then perform various calculations and changes for effective and long-term planning of construction. The mathematical simulation should show that some variants of machines combinations fail to accomplish the task under the given conditions, some will not be optimal in terms of costs or other parameters, other variants will be optimal in the view of costs required to fulfill the construction task. The simulation software allows a look at the results in graphical form or to export data to other programs. Application of the queues theory allows the introduction into the system waiting time the servicing elements and to approximate the mathematical model to a real working tasks on site.

The present paper deals with pollutants in the building’s indoor environment and possibilities of their elimination, carbon dioxide (CAS 124-38-9), further from volatile organic compounds were investigated trichlorethylene (CAS 79-01-6), toluene (CAS 108-88-3) and benzene (CAS 71-43-2). A new experimental method for effectively reducing the concentration of pollutants in the indoor environment of buildings is presented, which is based on the placement of plants into the research area and has the potential to bring operating costs savings in the field of building ventilation. The issue is closely related to the increasing requirements for the healthiness of the indoor environment of building. Quality of the indoor environment is also assessed according to the quality of indoor air. Increased concentrations of pollutants in the indoor environment can have a negative impact on the human health for the building’s users. In the paper, the modelling of indoor ventilation is shown, where one model case examines the theoretical quantity requirement of ventilated indoor air without plants and the other model case examines the requirement for the amount of ventilated air in plant environment. For both models cases the same final value of pollutant concentrations was required. After the computational modelling, the results were compared to determine the percentage difference of the supply air demand. Based on the computational model, it was shown that selected plants can favourably influence the pollutant concentration in the indoor environment. The model environment for research was determined as an office area, initial concentrations of pollutants were determined before the arrival of persons, also was determined the constant production of pollutants during working hours, and reduction of pollutants by plants This is a completely new perspective on the issues of building ventilation and improving the quality of the indoor environment, and according to the achieved calculation, the costs of building operations on a global scale can be significantly reduced.

The article deals with the implementation of plants in the indoor environment of buildings to reduce the concentration of CO2. Based on a specified model representing the internal environment of an office space, it was studied whether the requirement for the total amount of ventilated air could be reduced by using plants, thereby achieving savings of operating costs in the building ventilation sector. The present research describes the effect of plant implementation according to different levels of CO2 concentration of the supply air, specifically with values of 410 ppm corresponding to the year 2020, 550 ppm to the year 2050 and 670 ppm to the year 2100, as well as according to different levels of CO2 concentration in the indoor environment, namely 1000 ppm and 1500 ppm, the illumination of plants in the indoor environment is constant in the model, PPFD equals to 200 μmolm−2 s−1. Based on the computational model, it was found that the implemented plants can positively influence the requirement for the total amount of ventilated air, the most significant effect is in the case of a low indoor environment quality, with the CO2 concentration of 1500 ppm, and a high supply air quality 410 p˙pm. The simulation also showed that compared to 2020, by the year 2100, it will be necessary to increase the ventilation of the indoor environment by 25.1% to ensure the same quality of the indoorenvironment.