Expert Systems and Multiple Criteria Decision Support

1991 ◽  
pp. 191-204
Author(s):  
J. Clímaco ◽  
C. H. Antunes ◽  
J. P. Costa ◽  
A. G. Martins ◽  
A. T. Almeida
Keyword(s):  
Decision Support ◽  
Expert Systems ◽  
Multiple Criteria

Assessing desalination as a sustainable alternative using a multiple criteria decision support model

2008 ◽  
Vol 3 (3) ◽  
Author(s):  
M. B. Fernandes ◽  
M. C. Almeida ◽  
A. G. Henriques
Keyword(s):  
Decision Support ◽  
Energy Production ◽  
Fossil Fuels ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
High Energy ◽  
Economic Benefits ◽  
Multiple Criteria ◽  
Water Production ◽  
Decision Support Model

Desalination technologies provide an alternative for potable water production, having significant potential for application where fresh water scarcity exists. Potential benefits have to be balanced with other factors, such as high costs, high energy consumption, and significant environmental impacts, for the understanding of real risks and gains of desalination within the context of integrated water resources management. Multiple factors can be considered when analysing the viability of a desalination project but often a limited approach is used. The complexity in the analysis lies in finding the alternatives that obey to multiple objectives (e.g. reduced environmental impact, social acceptance, less cost associated). In this paper, development of a methodology based on multiple criteria decision support system for the evaluation and ranking the potential of desalination technologies is described and applied to a Portuguese case study. Relevant factors to the selection of desalination technologies were identified using SWOT analysis and the MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) approach was applied. Technical alternatives considered include reverse osmosis and multi-effect desalination (MED), together with energy production by fossil fuels or solar energy. Production of water by conventional approaches was also considered. Results, for non-economic benefits, show higher score for MED solar but, in the cost-benefit analysis, conventional methods of water production have higher ranking since costs of renewable energies are not yet competitive. However, even if not preferred in economic terms, desalination is ranked significantly above the conventional approaches for non-economic criteria.

scholarly journals Knowledge Acquisition and Representation for High-Performance Building Design: A Review for Defining Requirements for Developing a Design Expert System

2021 ◽  
Vol 13 (9) ◽  
pp. 4640
Author(s):  
Seung-Yeoun Choi ◽  
Sean-Hay Kim
Keyword(s):  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Knowledge Acquisition ◽  
Data Analytics ◽  
High Performance ◽  
Problem Definition ◽  
Design Expert ◽  
Decision Support Process ◽  
High Performance Building

New functions and requirements of high performance building (HPB) being added and several regulations and certification conditions being reinforced steadily make it harder for designers to decide HPB designs alone. Although many designers wish to rely on HPB consultants for advice, not all projects can afford consultants. We expect that, in the near future, computer aids such as design expert systems can help designers by providing the role of HPB consultants. The effectiveness and success or failure of the solution offered by the expert system must be affected by the quality, systemic structure, resilience, and applicability of expert knowledge. This study aims to set the problem definition and category required for existing HPB designs, and to find the knowledge acquisition and representation methods that are the most suitable to the design expert system based on the literature review. The HPB design literature from the past 10 years revealed that the greatest features of knowledge acquisition and representation are the increasing proportion of computer-based data analytics using machine learning algorithms, whereas rules, frames, and cognitive maps that are derived from heuristics are conventional representation formalisms of traditional expert systems. Moreover, data analytics are applied to not only literally raw data from observations and measurement, but also discrete processed data as the results of simulations or composite rules in order to derive latent rule, hidden pattern, and trends. Furthermore, there is a clear trend that designers prefer the method that decision support tools propose a solution directly as optimizer does. This is due to the lack of resources and time for designers to execute performance evaluation and analysis of alternatives by themselves, even if they have sufficient experience on the HPB. However, because the risk and responsibility for the final design should be taken by designers solely, they are afraid of convenient black box decision making provided by machines. If the process of using the primary knowledge in which frame to reach the solution and how the solution is derived are transparently open to the designers, the solution made by the design expert system will be able to obtain more trust from designers. This transparent decision support process would comply with the requirement specified in a recent design study that designers prefer flexible design environments that give more creative control and freedom over design options, when compared to an automated optimization approach.

scholarly journals Teknik Pengambilan Keputusan Multi Kriteria Menggunakan Metode BAYES, MPE, CPI dan AHP

2011 ◽  
Vol 2 (1) ◽  
pp. 229
Author(s):  
Abdul Haris Rangkuti
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Multiple Criteria ◽  
Complex Dynamic ◽  
Bayes Method ◽  
Application Program ◽  
Structured Problems

Decision making at every company is something very important and vital. Decision making can be influenced by several aspects, so it can affect the promptness and accuracy of the process, especially when solving any complex, dynamic and less structured problems. Therefore, the combination of multiple criteria concept and an application program of decision-support system is an effective way to generate alternative decisions. The methods used for multiple criteria are: Bayes method, MPE, CPI and the AHP. This article discusses the use of each method, adapted to each problem. The four methods happen to be very effective with the help of the application program of decision support system. Expectantly these methods are able to assist company managements in decision-making. 

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