Artificial Intelligence
Combining belief functions when evidence conflicts
Decision Support Systems
Combining belief functions based on distance of evidence
Decision Support Systems
AIEIA: Software for fuzzy environmental impact assessment
Expert Systems with Applications: An International Journal
Analyzing the degree of conflict among belief functions
Artificial Intelligence
International Journal of Approximate Reasoning
Modeling contaminant intrusion in water distribution networks: A new similarity-based DST method
Expert Systems with Applications: An International Journal
A new linguistic MCDM method based on multiple-criterion data fusion
Expert Systems with Applications: An International Journal
An integrated fuzzy AHP-ELECTRE methodology for environmental impact assessment
Expert Systems with Applications: An International Journal
A new fuzzy dempster MCDM method and its application in supplier selection
Expert Systems with Applications: An International Journal
Assessment of E-Commerce security using AHP and evidential reasoning
Expert Systems with Applications: An International Journal
Evaluating Sensor Reliability in Classification Problems Based on Evidence Theory
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Risk analysis in a linguistic environment: A fuzzy evidential reasoning-based approach
Expert Systems with Applications: An International Journal
Knowledge-Based Systems
FUZZY SENSOR FUSION BASED ON EVIDENCE THEORY AND ITS APPLICATION
Applied Artificial Intelligence
A new method to determine basic probability assignment from training data
Knowledge-Based Systems
Supplier selection using AHP methodology extended by D numbers
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Environmental impact assessment (EIA) is a complex problem influenced by many aspects, such as environmental, social, economic, etc. Due to the involvement of human judgment, various uncertainties are introduced in the EIA process. One critical issue of EIA is the representation and handling of uncertain information. Many different theories are available to deal with uncertainty, however, deficiencies exist in these theories. In this paper, based on a more effective representation of uncertainty, called D numbers, a new method is proposed for the EIA problem. In the proposed method, the assessment results of environmental impacts are expressed and modeled by D numbers. An illustrative case is provided to demonstrate the effectiveness of the proposed method.