Risk management in construction industry in several cases is not only incomplete regarding the unification of Occupational Health and Safety (OHS) hazards, but it is also incomplete in not having a systematic and innovative method to assess the impacts of these risks on the objectives of a project. An integrated hybrid Fuzzy Inference System-Latin Hypercube Simulation for the evaluation of OHS risks in construction projects is presented in this paper. Prioritization of safety risks systematically without human interference with fuzzy inference system gives the appropriate response to the identified risks. An advanced Monte Carlo simulation is also used for the evaluation of quantitative objectives of a project. This approach allows us to get away from discrimination and simulate the risks with high impacts but with low probabilities. In order to measure the relationship between the occurrences of each of the risks impacts on project objectives, the sensitivity analysis based on Pearson correlation coefficient is used to determine the usefulness of the proposed integrated hybrid method.

In the past, different methods for asset depreciation have been defined but most of these procedures deal with certain parameters and inputs. The availability of certain parameters in many real world situations is difficult and sometimes impossible. The primary objective of this paper is to obtain methods for calculating depreciation where some of the defined parameters are under uncertainty. Hence, by using the fuzzy science basics, extension principle and ?-cut technique, we rewrite some classic methods for calculating depreciation in fuzzy form. Then, for comparing the methods of fuzzy depreciation under uncertain conditions by using the formula of calculating the Fuzzy Present worth (FPW), the Present worth of Tax saving (PWTS) of any aforementioned methods has been obtained. Finally, since the amount of tax savings achieved for each of the methods is a fuzzy number, one of the fuzzy prioritization methods is used in order to select the best depreciation technique.