Title :
Emerging artificial intelligence methodologies in uncertainty analysis and modeling
Author :
Attoh-Okine, N.O. ; Orji, Cyril
Author_Institution :
Dept. of Civil & Environ. Eng., Florida Int. Univ., Miami, FL, USA
Abstract :
This paper presents an introductory overview of various methods used in representing and solving uncertainty problems. The emerging methods help us to capture both the subjective judgment and incomplete information and data in decision analysis under uncertainty. The type of method to be used for a problem depends on the situation. Although, the emerging methods appear to address uncertainty very well, problems are usually encountered. The emerging methods involve complicated mathematics, which are fairly difficult to understand and handle for the average transportation and pavement engineer. As the sample space grows, it becomes very difficult to handle and analyze uncertainties using the emerging methods. The solution becomes difficult and labor intensive. The availability of software will be a very promising step. Some of the emerging methods like influence diagrams and valuation-based systems handle asymmetric problems
Keywords :
decision theory; fuzzy set theory; probability; uncertainty handling; artificial intelligence methodologies; asymmetric problems; complicated mathematics; decision analysis; decision trees; fuzzy measures; fuzzy sets; incomplete information; influence diagrams; modeling; probability theory; software; subjective judgment; uncertainty analysis; valuation-based systems; Artificial intelligence; Computer science; Decision trees; Entropy; Frequency; Fuzzy sets; Game theory; Humans; Measurement uncertainty; Numerical models;
Conference_Titel :
Southcon/95. Conference Record
Conference_Location :
Fort Lauderdale, FL
Print_ISBN :
0-7803-2576-1
DOI :
10.1109/SOUTHC.1995.516139