Abstract
The purpose of this article is to assess risk in order to substantiate the economic and organizational efficiency of housing and industrial construction. The authors study methods related to quantifying environmental risk and making decisions under conditions of uncertainty. An algorithm for making sound decisions is proposed as a result of a quantitative analysis of the identified risks. A quantitative risk assessment of pessimistic and optimistic options for preventing environmental damage was made using the Monte Carlo method. The results of simulation modeling clearly illustrate the choice of the general principle of assessment and adoption of the optimal decision. The results of a sensitivity analysis are also presented to prove the hypothesis. This risk analysis technique has a computer implementation. The result of Monte Carlo modeling is a graphical representation of the log-normal probability distribution of possible outcomes of the preset emergency scenarios in the form of a curve on a scalable field of the estimated consequences. The model has reproduced the distribution derived from the evidence-based data selection. The Monte Carlo method is one of the scientifically based methods for analyzing the characteristics of a random process and making optimal decisions in order to reduce risk and minimize environmental damage. It could become the desired basis for interaction between the State Environmental Expert Review (SEER) and environmental impact assessment (EIA) in order to make sound decisions and actions in conditions of uncertainty and choosing environmentally friendly options for economic projects.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call