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Risk management of engineering project is a complicated uncertainty problem. Based on the theory of set pair analysis (SPA), stochastic simulation of triangular fuzzy numbers, herein, a novel analysis model for the project risk management was discussed. A concept of multi-element connection number of the set pair was introduced to express the hierarchy and fuzziness of membership between the evaluation...
This paper applies a simple multiple regression based model to analyze financial data. The model uses a dummy variable as the dependent variable which could be interpreted as a predictor. The independent variables of the model are quantitative as well as qualitative. The results of the analysis support the predictive capability of the model.
Banks and investment funds are increasingly basing their competitiveness on the quality of their quantitative technology, including programming techniques, analytical methods, and applications such as financial forecasting, option pricing, and risk management, which are all essential elements of the field of computational finance.
This paper presents an application of the modeling and simulation methodology along with the Design of Experiments (DOE) to aid the decision makers to know the economic risk they are taking when there are many scenarios. Firstly, the production process was studied and documented by a SIPOC, an IDEF0 and a Flowchart. These techniques were combined to elaborate the simulation conceptual model. After...
Constantly evolving business requirements and the large amounts of data involved in concurrent engineering projects are challenges that managers face in managing project risks. This paper proposes an information modeling approach that can be used for the construction of risk models and lessons learnt. Using these models, rapid prototypes can be developed and deployed within a Web-based risk management...
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