An Improvement of decision making for project risk assessment using the fuzzy logic concept

VALIDATION AND DISCUSSION Sensitivity analysis of the model To get a better level of confidence about the model that we designed, a simple sensitivity analysis has been made. In order to evaluate the value of sensitivity analysis first the model needs to be tested by validation against other results elsewhere. So we choose as a […]

Step 5: Final risk level and Interpretation In this step, the decision maker will appreciate the final value of the project risk, and give some explanations about it. For each value of the risk corresponds a suitable interpretation that will be used further in the overall risk management. Final risk level The system output variable

Step 3: Risk level measurement Projects with high-impact/low- probability risks need to be continually monitored to make sure the risk probabilities don’t change, Taylor says. If the probability of a high-impact event increases, there should be no debate as to what that means for the project. This is why this step is somehow undefeatable for

AN IMPROVED FUZZY MODEL FOR PROJECT RISK ASSESSMENT A brief Summary of the proposed Approach The purpose of this study is to design and develop a Fuzzy decision making support model to assist project managers in identifying potential risk factors and evaluating the corresponding development risks. Different approaches have been created to assess the various

CURRENT APPROACHES FOR DECISION MAKING IN SOLAR ENERGY PROJECT RISK ASSESSMENT General situation of solar energy risk assessment The use of photovoltaic (PV) solar systems for the generation of electric power has increased dramatically All over the world in recent years. The reason for this has been, on the one hand, the recent development of

Fuzzy logic theory and systems Introduction to fuzzy logic Background To deal with vagueness in human thought, Lotfi A. Zadeh (1965) first introduced the fuzzy set theory, which has the capability to represent and manipulate data and information possessing based on non-statistical uncertainties. Moreover fuzzy set theory has been designed to mathematically represent uncertainty and