Titlebook: Expert Systems and Artificial Intelligence in Decision Support Systems; Proceedings of the S Henk G. Sol,Cees A. Th. Takkenberg,Pieter F. V

HEIR

書目名稱Expert Systems and Artificial Intelligence in Decision Support Systems影響因子(影響力)




書目名稱Expert Systems and Artificial Intelligence in Decision Support Systems影響因子(影響力)學(xué)科排名




書目名稱Expert Systems and Artificial Intelligence in Decision Support Systems網(wǎng)絡(luò)公開度




書目名稱Expert Systems and Artificial Intelligence in Decision Support Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Expert Systems and Artificial Intelligence in Decision Support Systems被引頻次




書目名稱Expert Systems and Artificial Intelligence in Decision Support Systems被引頻次學(xué)科排名




書目名稱Expert Systems and Artificial Intelligence in Decision Support Systems年度引用




書目名稱Expert Systems and Artificial Intelligence in Decision Support Systems年度引用學(xué)科排名




書目名稱Expert Systems and Artificial Intelligence in Decision Support Systems讀者反饋




書目名稱Expert Systems and Artificial Intelligence in Decision Support Systems讀者反饋學(xué)科排名

弄皺

Models: Operational, Expert, and Intelligent,ugh its expert systems (ES) approaches has recently begun to attack similar problems. I believe that AI/ES and OR applications have similar objectives to permit the executive or decision maker to improve his understanding of, and take desirable actions in a particular operational domain. Both must b

語源學(xué)

膝蓋

季雨

Responsive Decision Support Systems: A Broad View Illustrates When to Include Expert Systems,ls and their relationships with the manager and his or her operation. To realize its full potential, view a decision support system top-down, from the manager’s perspective. The model gives us a broad view so that we can compare decision support systems (DSS), management information systems (MIS), e

Assemble

A Logic Programming Approach to Building Planning and Simulation Models,xpert systems. These tools may also benefit more traditional management science applications such as planning and simulation. A framework is proposed for describing the problem domain (’model base’) of planning and simulation problems in logical form, separate from the inferencing mechanisms applied

Assemble

Knowledge-Based Formulation of Linear Planning Models,aker in modelling unanticipated planning problems efficiently without the support of scarce operations research specialists. A major contribution towards the development of model formation subsystems in DSS is expected from the use of Artificial Intelligence (AI) techniques. However, it is claimed i

白楊魚

Linguistic Exploratory Analysis for Decision Support, The computer software technique employed here stems from the use of fuzzy sets. This technique will be explained and an example of its application will be given: linguistic exploratory (’what if’) analysis.

擴(kuò)大

Modelling Support Environments,rocess, a person is needed, who extracts the users’ knowledge of the problem domain, decides on a suitable algorithm (if existent), designs a model and expresses the model in a form which is suitable for the chosen algorithm. In order to make users independant and willing to accept models and their

micronized

Heuristics in the Abbot-Monk Problem, careful examination of its organizational structure with respect to the relations between processes and data structures can result in a performance improvement. The appropriate tool for investigating parallel systems is simulation. In order to get some insight into the inter-dependency of the proce