High Risk Management Model For The Power Enterprise Based on Rough Set Theory

Zhiyao, Li; Wang, Moyu; Ma, Xinke; Xiaoliu, Shen

doi:10.1016/j.sepro.2011.11.009

Cited by 6 publications

(3 citation statements)

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“…(2020) proposed a two-stage grey cloud clustering model to assess the drought risk level of 18 prefecture-level cities. Zhiyao et al . (2012) proposed a high-risk customer management model based on RST.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Luo et al (2020) proposed a two-stage grey cloud clustering model to assess the drought risk level of 18 prefecture-level cities. Zhiyao et al (2012) proposed a high-risk customer management model based on RST. They briefly analyzed the characteristics and application of RST and then gave a method to reduce the irrelevant indicators before generating rules.…”

Section: Literature Reviewmentioning

confidence: 99%

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Developing a risk assessment model for banking software development projects based on rough-grey set theory

Karimi

Yahyazade

2021

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PurposeRisk management is one of the most influential parts of project management that has a major impact on the success or failure of projects. Due to the increasing use of information technology in all fields and the high failure rate of software development projects, it is essential to predict the risk level of each project effectively before starting. Therefore, the main purpose of this paper is proposing an expert system to infer about the risk of new banking software development project.Design/methodology/approachIn this research, the risk of software developing projects is considered from four dimensions including risk of cost deviation, time deviation, quality deviation and scope deviation, which is examined by rough set theory (RST). The most important variables affecting the cost, time, quality and scope of projects are identified as condition attributes and four initial decision systems are constructed. Grey system theory is used to cluster the condition attributes and after data discretizing, eight rule models for each dimension of risk as a decision attribute are extracted using RST. The most validated model for each decision attribute is selected as an inference engine of the expert system, and finally a simple user interface is designed in order to predict the risk level of any new project by inserting the data of project attributesFindingsIn this paper, a high accuracy expert system is designed based on the combination of the grey clustering method and rough set modeling to predict the risks of each project before starting. Cross-validation of different rule models shows that the best model for determining cost deviation is Manual/Jonson/ORR model, and the most validated models for predicting the risk of time, quality and scope of projects are Entropy/Genetic/ORR, Manual/Genetic/FOR and Entropy/Genetic/ORR models; all of which are more than 90% accurateResearch limitations/implicationsIt is essential to gather data of previous cases to design a validated expert system. Since data documentation in the field of software development projects is not complete enough, grey set theory (GST) and RST are combined to improve the validity of the rule model. The proposed expert system can be used for risk assessment of new banking software projectsOriginality/valueThe risk assessment of software developing projects based on RST is a new approach in the field of risk management. Furthermore, using the grey clustering for combining the condition attributes is a novel solution for improving the accuracy of the rule models.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Developing a risk assessment model for banking software development projects based on rough-grey set theory

Karimi

Yahyazade

2021

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“…Zhiyao et al proposed a high-risk customer management model based on rough set theory to overcome the weakness of traditional risk management model in processing historical data efficiently. They proposed a method to reduce the irrelevant indicators before generating rules using rough set and combined risk management and rough set theory in a good way to process the historical data (Zhiyao, Wang Moyu, Ma Xinke, & Xiaoliu, 2012).…”

Section: Introductionmentioning

confidence: 99%

A Novel Conceptual Risk Management Model Based on The Future’s Uncertainties

Hafezi¹,

Akhavan²

2019

Preprint

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Controlling and managing risk is always a critical point for the managers, investors and even consultants. Having clear and better percepts about future can reduce the risk of fail. In addition it is important for a risk analyzer to consider the stakeholders views and senses about the risk. This research aimed at framing a comprehensive risk management model which builds up on stakeholder requirements and forecasting techniques. This conceptual model attempts to use the stakeholder’s points of view to write prefer and probable scenarios to neglect critical risks and increase the chance of success in long-term plannings. Using futures studies methods prepare decision makers for the possible upcoming events and donate them a powerful tool to handle the uncertainties cover the future.

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An entropy-based uncertainty measurement approach in neighborhood systems

Chen

et al. 2014

Information Sciences

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High Risk Management Model For The Power Enterprise Based on Rough Set Theory

Cited by 6 publications

References 1 publication

Developing a risk assessment model for banking software development projects based on rough-grey set theory

Developing a risk assessment model for banking software development projects based on rough-grey set theory

A Novel Conceptual Risk Management Model Based on The Future’s Uncertainties

An entropy-based uncertainty measurement approach in neighborhood systems

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High Risk Management Model For The Power Enterprise Based on Rough Set Theory

Cited by 6 publications

References 1 publication

Developing a risk assessment model for banking software development projects based on rough-grey set theory

Developing a risk assessment model for banking software development projects based on rough-grey set theory

A Novel Conceptual Risk Management Model Based on The Future&rsquo;s Uncertainties

An entropy-based uncertainty measurement approach in neighborhood systems

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A Novel Conceptual Risk Management Model Based on The Future’s Uncertainties