scholarly journals Development of a hybrid AHP and Dempster-Shafer theory of evidence for project risk assessment problem

2022 ◽  
Vol 7 (2) ◽  
pp. 77-94
Author(s):  
Saad M. Albogami ◽  
Mohd Khairol Anuar Bin Mohd Ariffin ◽  
Eris Elianddy Bin Supeni ◽  
Kamarul Arifin Ahmad
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Taguchi Method ◽  
Risk Indicator ◽  
Project Risk ◽  
Strategic Risk ◽  
Dempster Shafer Theory ◽  
Shafer Theory ◽  
Theory Of Evidence ◽  
Reduced Risk

In this paper, a new hybrid AHP and Dempster-Shafer Theory of Evidence is presented for solving the problem of choosing the best project among a list of available alternatives while uncertain risk factors are taken into account. The aim is to minimize overall risks. For this purpose, four groups of risk factors, including Properties, Operational and Technological, Financial, Strategic risk factors, are considered. Then using an L24 Taguchi method, several experiments with various dimensions have been designed and solved by the proposed algorithm. The outcomes are then analyzed using the Validating Index (VI), Reduced Risk Indicator (R.R.I%), and Solving time. The findings indicated that, compared to the classic AHP, the results of the proposed hybrid method were different in most cases due to uncertainty of risk factors. It was observed that the method could be safely used for selecting project problems in real industries.

scholarly journals A New Hybrid AHP and Dempster—Shafer Theory of Evidence Method for Project Risk Assessment Problem

Mathematics ◽  
2021 ◽  
Vol 9 (24) ◽  
pp. 3225
Author(s):  
Saad Muslet Albogami ◽  
Mohd Khairol Anuar Bin Mohd Ariffin ◽  
Eris Elianddy Bin Supeni ◽  
Kamarul Arifin Ahmad
Keyword(s):  
Risk Factors ◽  
Quantitative Research ◽  
Learning Algorithm ◽  
Risk Indicator ◽  
Strategic Risk ◽  
The Third ◽  
Dempster Shafer Theory ◽  
Three Phase ◽  
Shafer Theory ◽  
Theory Of Evidence

In this paper, a new hybrid AHP and Dempster—Shafer theory of evidence is presented for solving the problem of choosing the best project among a list of available alternatives while uncertain risk factors are taken into account. The aim is to minimize overall risks. For this purpose, a three-phase framework is proposed. In the first phase, quantitative research was conducted to identify the risk factors that can influence a project. Then, a hybrid PCA-agglomerative unsupervised machine learning algorithm is proposed to classify the projects in terms of Properties, Operational and Technological, Financial, and Strategic risk factors. In the third step, a hybrid AHP and Dempster—Shafer theory of evidence is presented to select the best alternative with the lowest level of overall risks. As a result, four groups of risk factors, including Properties, Operational and Technological, Financial, and Strategic risk factors, are considered. Afterward, using an L2^4 Taguchi method, several experiments with various dimensions have been designed which are then solved by the proposed algorithm. The outcomes are then analyzed using the Validating Index, Reduced Risk Indicator, and Solving Time. The findings indicated that, compared to classic AHP, the results of the proposed hybrid method were different in most cases due to uncertainty of risk factors. It was observed that the method could be safely used for selecting project problems in real industries.

scholarly journals An Evidential Model for Environmental Risk Assessment in Projects Using Dempster–Shafer Theory of Evidence

2019 ◽  
Vol 11 (22) ◽  
pp. 6329 ◽  
Author(s):  
Hatefi ◽  
Basiri ◽  
Tamošaitienė
Keyword(s):  
Risk Assessment ◽  
Sustainable Development ◽  
Environmental Risk ◽  
Environmental Risk Assessment ◽  
Fuzzy Inference ◽  
Inference System ◽  
Dempster Shafer Theory ◽  
Proposed Model ◽  
Shafer Theory ◽  
Theory Of Evidence

One of the goals of sustainable development is to achieve economic and social growth according to environmental criteria. Nowadays, impact assessment is an efficient decision making method in planning and management with environmental perspectives. Environmental risk assessment is a tool to reduce the impacts and consequences of various activities on the environment in order to achieve sustainable development. One of the commonly used environmental risk assessment methods is the probability–impact matrix method, which is known as a quantitative method for risk assessment of projects. In this method, numerical estimates of probability and impact of risk occurrence are very difficult, and these factors are associated with uncertainty. When uncertainty exists, data integration is of great importance, for which the fuzzy inference system and evidence theory are known as effective methods. Unavailability of experts’ opinion and the exponential growth of the number of required fuzzy rules associated with the risk factors are two drawbacks of fuzzy inference. Dempster–Shafer’s theory of evidence is one of the popular theories used in intelligent systems for modeling and reasoning under uncertainty and inaccuracy. In this paper, an evidential model for project environmental risk assessment is proposed based on the Dempster–Shafer theory, which is capable of taking into account the uncertainties. The proposed model is used to assess the environmental risks of Maroon oil pipelines in Isfahan. In addition, the proposed model is used in the case of tunneling risk assessment taken from the subject literature. To evaluate the validity of the proposed evidential model, the results are compared in two case studies, with the results of the conventional risk assessment method and the fuzzy inference system method. The comparative results show that the proposed model has a high potential for project risk assessment under an uncertain environment.

scholarly journals The CUORE project cardiovascular risk assessment in primary care: the ongoing experience in Italy

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
L Palmieri ◽  
S Vannucchi ◽  
C Lo Noce ◽  
A Di Lonardo ◽  
B Unim ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Risk Assessment ◽  
Primary Care ◽  
Cardiovascular Risk ◽  
Risk Score ◽  
Adult Population ◽  
Cardiovascular Risk Assessment ◽  
Project Risk ◽  
Preventive Actions

Abstract Background Italian National Prevention Plan 2005-08 included 10-year cardiovascular risk assessment (10-CR) for the general population aged 35-69 years using the CUORE Project risk score. GPs were encouraged to perform 10-CR and send data to the Cardiovascular Risk Observatory (CRO). Aim To show updated data of the ongoing surveillance system of the 10-CR in the Italian adult population. Methods Data were collected using the cuore.exe software, freely downloadable by GPs from the CUORE Project website (www.cuore.iss.it). The CRO provides a web-platform to compare data on 10-CR and risk factors at regional/national level. For persons examined at least twice, variations in risk factors from baseline to follow-up and 95% confidence intervals (C.I.) were calculated using methods for matched pair samples. Results Up to February 2019, about 3,500 GPs downloaded cuore.exe; about 300,000 CR assessments on about 140,000 persons were sent to CRO. Mean CR was 3.1% in women (W), 8.5% in men (M); 28% of M, 64% of W were at low risk (CR < 3%); 9.9% of M, 0.4% of W were at high risk (CR ≥ 20%); 26% of M, 16% of W were current smokers; 13% of M, 10% of W were diabetic; 33% of hypertensive M, 35% of hypertensive W were under specific treatment. Among those with at least two risk assessments (31% of the sample), 11% shifted to a lower risk class after one year (14% of M, 7% of W). Systolic blood pressure mean levels decreased by 0.6 mmHg (95%-C.I. 0.3-0.8 mmHg), diastolic blood pressure by 0.5 mmHg (0.2-0.7 mmHg), total cholesterol by 4.1 mg/dl (3.0-5.2 mg/dl), smokers prevalence by 3.1% (2.3%-4.0%); HDL-cholesterol increased in W by 0.3 mg/dl (0.1-0.5 mg/dl). Conclusions Data demonstrate that 10-CR assessment can be an effective first step to implement preventive actions in primary care. Individual risk score is a useful tool for GPs to assess CR and promote primary prevention focusing on the adoption of healthy lifestyles. Data can be used to support health policy decision process. Key messages The cuore.exe software, freely downloadable from the CUORE Project website-www.cuore.iss.it, allows GPs to assess the CUORE Project risk score, to collect and to send data to the CVD Risk Observatory. 10 year Cardiovascular Risk assessment in the general adult population can be an effective first step to implement preventive actions in primary care.

scholarly journals A MODIFIED D NUMBERS METHODOLOGY FOR ENVIRONMENTAL IMPACT ASSESSMENT

2017 ◽  
Vol 24 (2) ◽  
pp. 653-669 ◽  
Author(s):  
Ningkui WANG ◽  
Daijun WEI
Keyword(s):  
Environmental Impact ◽  
Impact Assessment ◽  
Environmental Impact Assessment ◽  
Previous Method ◽  
Combination Process ◽  
Dempster Shafer Theory ◽  
Shafer Theory ◽  
Theory Of Evidence ◽  
D Numbers ◽  
Commutative Property

Environmental impact assessment (EIA) is usually evaluated by many factors influenced by various kinds of uncertainty or fuzziness. As a result, the key issues of EIA problem are to rep­resent and deal with the uncertain or fuzzy information. D numbers theory, as the extension of Dempster-Shafer theory of evidence, is a desirable tool that can express uncertainty and fuzziness, both complete and incomplete, quantitative or qualitative. However, some shortcomings do exist in D numbers combination process, the commutative property is not well considered when multiple D numbers are combined. Though some attempts have made to solve this problem, the previous method is not appropriate and convenience as more information about the given evaluations rep­resented by D numbers are needed. In this paper, a data-driven D numbers combination rule is proposed, commutative property is well considered in the proposed method. In the combination process, there does not require any new information except the original D numbers. An illustrative example is provided to demonstrate the effectiveness of the method.

Knowledge reduction in random information systems via Dempster–Shafer theory of evidence

2005 ◽  
Vol 174 (3-4) ◽  
pp. 143-164 ◽  
Author(s):  
Wei-Zhi Wu ◽  
Mei Zhang ◽  
Huai-Zu Li ◽  
Ju-Sheng Mi
Keyword(s):  
Information Systems ◽  
Knowledge Reduction ◽  
Dempster Shafer Theory ◽  
Shafer Theory ◽  
Theory Of Evidence
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