Titlebook: Intelligent Decision-making Support Systems; Foundations, Applica Jatinder N. D. Gupta,Guisseppi A. Forgionne,Manuel Book 2006 Springer-Ver

CBC471

laparoscopy

混合,搀杂

Peter Braun,Jakub Brzostowski,Gregory Kersten,Jin Baek Kim,Ryszard Kowalczyk,Stefan Strecker,Rustam

alcoholism

流利圆滑

A Multicriteria Model for the Evaluation of Intelligent Decision-making Support Systems (i-DMSS)ed, and no studies have focused exclusively on categories for the evaluation of i-DMSS. This chapter explores the concept of intelligence in general, and artificial intelligence in particular, as it relates to aiding decision making. It then proposes an architecture for the evaluation of i-DMSS and

Soliloquy

Synergizing the Artificial Intelligence and Decision Support Research Streams: Over a Decade of Proggent decision support, and the new domain brings with it new challenges and opportunities. We look to patterns in both the maturing streams of individual, team, and organizational intelligent decision support, as well as those emerging in the new interorganizational stream, to propose direction for

刚开始

gimmick

A Causal Knowledge-driven Negotiation Mechanism for B2B Electronic Commercen order to examine the validity of our proposed mechanism. The mechanism was tested using two practical scenarios: a structured, twenty-one item questionnaire was developed and applied in order to evaluate the mechanism’s validity based on the responses of eleven graduate students. In addition, stat

窝转脊椎动物

An i-DMSS Based on Bipartite Matching and Heuristics for Rental Bus Allocationhis i-DMSS is used to make the decisions daily. The i-DMSS is based on bipartite matching and transportation algorithms and heuristics, and produces solutions 10–20% more economical than the manual decisions.

CLOUT