Fuzzy Evaluation Method for Project Profitability

Ali, Rekik; Mounir, Gabsi; Balas, Valentina E.; Nissen, Masmoudi

doi:10.1007/978-3-319-45991-2_2

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…The venture the board issue is settled utilizing an improvement task that is unsure and vulnerable to genuine constraints [40]. We utilize likelihood hypothesis and approaches that are not very much demonstrated; yet, because of an absence of information, we really want to apply elective strategies to decide the most ideal way to assess vulnerability.…”

Section: Use Of Fuzzy Evaluation Methods For Risk Assessmentmentioning

confidence: 99%

A Fuzzy Evaluation Method Based on Industrial Cluster Investment Risk Assessment Method Based on IoT Applications

Zhang

2022

Wireless Communications and Mobile Computing

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Hazard evaluation and the board are logical subject that goes back 30-40 years. For how to conceptualize, investigate, and oversee hazard, standards and strategies were set up. These ideas that move toward still comprise a major piece of the field’s premise today, despite the fact that there have been numerous progressions in both the hypothetical stage and functional models and cycles. The nonlinear properties of the appraisal cycle give the premise to fluffy assessment. It measures and incorporates the nonlinear assessment area utilizing the fluffy activity rule in fluffy math, bringing about a quantitative appraisal strategy that is practically identical. Modern bunch estimation and evaluation are vital parts of modern group hypothesis research; in any case, they do not stand out enough to be noticed. Modern bunch hazard factors are extremely indistinct, and common assessment and estimating approaches have restrictions. Thus, this work, which depends on fluffy mathematic hypothesis, utilizes an updated fluffy far reaching strategy to exhaustively research and assess modern group hazard and foster a danger appraisal model.

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Section: Use Of Fuzzy Evaluation Methods For Risk Assessmentmentioning

confidence: 99%

A Fuzzy Evaluation Method Based on Industrial Cluster Investment Risk Assessment Method Based on IoT Applications

Zhang

2022

Wireless Communications and Mobile Computing

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“…Moreover, Costantino et al [129] provided an ANN-based decision support system to predict project performances for project selection, which relates critical success factors with project success by classifying the level of a project's riskiness via the experiences of project managers. Furthermore, the article [130] employs fuzzy decision making for project selection under uncertainty.…”

Section: Uncertainty Pdmentioning

confidence: 99%

Artificial Intelligence Enabled Project Management: A Systematic Literature Review

et al. 2023

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In the Industry 5.0 era, companies are leveraging the potential of cutting-edge technologies such as artificial intelligence for more efficient and green human-centric production. In a similar approach, project management would benefit from artificial intelligence in order to achieve project goals by improving project performance, and consequently, reaching higher sustainable success. In this context, this paper examines the role of artificial intelligence in emerging project management through a systematic literature review; the applications of AI techniques in the project management performance domains are presented. The results show that the number of influential publications on artificial intelligence-enabled project management has increased significantly over the last decade. The findings indicate that artificial intelligence, predominantly machine learning, can be considerably useful in the management of construction and IT projects; it is notably encouraging for enhancing the planning, measurement, and uncertainty performance domains by providing promising forecasting and decision-making capabilities.

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“…The risk assessment of innovative project is related to the optimization task under uncertainty and risk [5]. To invest in innovative projects, companies must have a various strategies; these strategies must reach an effective level of coherence through a variety of decisions [4,7].…”

Section: Introductionmentioning

confidence: 99%

A New Approach for Forming a Probabilistic Risk Assessment Model of Innovative Project Implementation Under Risk

Ali¹,

Nissen

2018

2018 IEEE Second International Conference on Data Stream Mining &Amp; Processing (DSMP)

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In this paper we propose a new approach for constructing a probabilistic risk assessment model of innovative project. The method is based on the task of comparison and ranking of fuzzy numbers that has an important role in more applications related to the decision analysis. In the literature there are many approaches to compare fuzzy numbers. The majority of these approaches are based on the quantitative measurements. For that, we propose a new method to calculate the risk level that we can accord to equality X

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Fuzzy Evaluation Method for Project Profitability

Cited by 3 publications

References 14 publications

A Fuzzy Evaluation Method Based on Industrial Cluster Investment Risk Assessment Method Based on IoT Applications

A Fuzzy Evaluation Method Based on Industrial Cluster Investment Risk Assessment Method Based on IoT Applications

Artificial Intelligence Enabled Project Management: A Systematic Literature Review

A New Approach for Forming a Probabilistic Risk Assessment Model of Innovative Project Implementation Under Risk

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