Decision Models Evaluation Using Fuzzy Pattern Recognition
Artificial intelligent models such as Artificial Neural Network, Genetic Algorithms, etc., play important roles in decision making. However, diversity in natures of intelligent models makes it difficult to decide which model is the most suitable one in solving certain decision problems. This paper proposes criteria of deferent suitability levels to evaluate the suitability of intelligent methods to decision environments, and presents a procedural method to calculate the suitability levels using Fuzzy Pattern Recognition. It analyzes various attributes related to decision problems and decision support systems’ performance, then proposes a term SMP (Suitability of Model to decision Problem) for evaluating the suitability of decision models to certain decision problems. The influences of various attributes and preferences of decision makers are further explored, and a concept of SSMP (Synthetic SMP) is proposed to address human aspects in decision making. The paper presents a procedural method to calculate SMP and SSMP. Experimental calculation result shows this method is applicable in decision models selection.
Minglun Ren Juanjuan Duan Shanlin Yang
School of Management, Hefei University of Technology Hefei 230009, P.R.China
国际会议
2007年IEEE灰色系统与智能服务国际会议(2007 IEEE International Conference on Grey Systems and Intelligent Services)
南京
英文
2007-11-18（万方平台首次上网日期，不代表论文的发表时间）