Monte Carlo based Risk Analysis of Unmanned Aerial Vehicle Flights over Construction Job Sites

Moud, Hashem Izadi; Shojaei, Alireza; Flood, Ian; Zhang, Xun

doi:10.5220/0006868804510458

Cited by 14 publications

(8 citation statements)

References 24 publications

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“…A wide range of studies have been conducted regarding risk or performance analysis on multiple watersheds, dams or tunnels all around the world with a diverse hydro-climatological regimes [25][26][27][28][29][30][31][32][33]. Anane et al (2012) carried out a study to prioritize the best locations for irrigation with treated wastewater (TWW) in Tunisia [34].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of the AHP and TOPSIS Techniques for Dam Site Selection Using GIS: A Case Study of Sistan and Baluchestan Province, Iran

et al. 2018

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The application of multiple criteria decision-making (MCDM) techniques in real-life problems has increased in recent years. The need to build advanced decision models with higher capabilities that can support decision-making in a broad spectrum of applications, promotes the integration of MCDM techniques with applicable systems, including artificial intelligence, and Geographic Information Systems (GIS). The Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are among the most widely adopted MCDM techniques capable of resolving water resources challenges. A critical problem associated with water resource management is dam site selection. This paper presents a comparative analysis of TOPSIS and AHP in the context of decision-making using GIS for dam site selection. The comparison was made based on geographic and water quality criteria. The geographical criteria are geology, land use, sediment, erosion, slope, groundwater, and discharge. The water quality criteria include Soluble Sodium Percentage, Total Dissolved Solid, Potential of Hydrogen, and Electrical Conductivity of water. A ratio estimation procedure was used to determine the weights of these criteria. Both methods were applied for selection of optimal sites for dams in the Sistan and Baluchestan province, Iran. The results show that the TOPSIS method is better suited to the problem of dam site selection for this study area. Actual locations of dams constructed in the area were used to verify the results of both methods.

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Section: Introductionmentioning

confidence: 99%

A Comparative Study of the AHP and TOPSIS Techniques for Dam Site Selection Using GIS: A Case Study of Sistan and Baluchestan Province, Iran

et al. 2018

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“…After the organization of the NPV function, the uncertain variables are identified, then, if sufficient historical data are available, the appropriate probability distributions for the considered variables are included. The Monte Carlo method is used to generate the random numbers to model the probability distribution of the corresponded variables [30][31][32]. Finally, the probability distributions of the variables are included in the NPV function using the Monte Carlo method and the probability distribution of the NPV is obtained by discounting the probability distribution of the cash flows.…”

Section: Modelingmentioning

confidence: 99%

Development of an ESCO Risk Assessment Model as a Decision-Making Tool for the Energy Savings Certificates Market Regulator: A Case Study

et al. 2020

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This article is focused on developing an Energy Service Company (ESCO) risk assessment model for use by energy savings certificates (ESC) market regulators. This model enables market regulators to determine the appropriate point in time for ESCOs to sell their certificates with the aim of minimizing risk as well as maximizing economic gain yet remain motivated for reducing the cost of energy efficiency technologies. To this end, the interactions between an ESCO and other parties (such as suppliers) in the market in addition to the principles of the energy efficiency performance contract are taken into consideration. Then, appropriate probability distributions have been fitted to the stochastic variables to be applied in the Net Present Value (NPV) function, based on sampled company data. A case study considers a one MW Organic Rankine Cycle (ORC) implementation in Iran’s petrochemical industry. The finding of this study shows if the ESCO is allowed to sell the certificates during the first seven years as well reduce 30% of the investment cost, the expected Net Present Value over Investment Cost (NPV/I) savings will cover more than one cycle.

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“…Hayhurst et al (2006) have discussed hazards associated with UAV operations, by categorizing the hazards into three domainsthe UAV Design Domain, the UAV Flight Crew Domain, and the UAV Operational Domain. Moreover, Hashem Izadi, et al (Moud et al, 2018) have proposed a qualitative risk assessment for UAV flights by combining the Federal Aviation Administration (FAA) rules, regulations, and guidelines concerning UAV flights, with the safety needs and specifications of UAV flights on a construction job site. Furthermore, there are recent efforts to employ high-level AI techniques such as deep learning for hazard identifications, see e.g.…”

Section: Introductionmentioning

confidence: 99%

Hazards identification and risk assessment for UAV–assisted bridge inspections

Aliyari

Ashrafi

Ayele

2021

Structure and Infrastructure Engineering

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Monte Carlo based Risk Analysis of Unmanned Aerial Vehicle Flights over Construction Job Sites

Cited by 14 publications

References 24 publications

A Comparative Study of the AHP and TOPSIS Techniques for Dam Site Selection Using GIS: A Case Study of Sistan and Baluchestan Province, Iran

A Comparative Study of the AHP and TOPSIS Techniques for Dam Site Selection Using GIS: A Case Study of Sistan and Baluchestan Province, Iran

Development of an ESCO Risk Assessment Model as a Decision-Making Tool for the Energy Savings Certificates Market Regulator: A Case Study

Hazards identification and risk assessment for UAV–assisted bridge inspections

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