Automatic feature weighting for improving financial Decision Support Systems

2018 ◽  
Vol 107 ◽  
pp. 78-87 ◽  
Author(s):  
Yosimar Oswaldo Serrano-Silva ◽  
Yenny Villuendas-Rey ◽  
Cornelio Yáñez-Márquez
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Feature Weighting ◽  
Financial Decision

Designing personalized intelligent financial decision support systems

1999 ◽  
Vol 26 (1) ◽  
pp. 31-47 ◽  
Author(s):  
António Palma-dos-Reis ◽  
Fatemeh “Mariam” Zahedi
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Financial Decision

Topological applications of multilayer perceptrons and support vector machines in financial decision support systems

2018 ◽  
Vol 24 (1) ◽  
pp. 474-507 ◽  
Author(s):  
Mohammad Zoynul Abedin ◽  
Chi Guotai ◽  
Fahmida-E- Moula ◽  
A.S.M. Sohel Azad ◽  
Mohammed Shamim Uddin Khan
Keyword(s):  
Decision Support ◽  
Support Vector Machines ◽  
Decision Support Systems ◽  
Support Systems ◽  
Support Vector ◽  
Multilayer Perceptrons ◽  
Vector Machines ◽  
Financial Decision

scholarly journals Scoring models: Towards the more realistic approach

2009 ◽  
Vol 6 (1) ◽  
pp. 45-69 ◽  
Author(s):  
Gordana Radojevic ◽  
Milija Suknovic
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Financial Management ◽  
Support Systems ◽  
Classical System ◽  
Problem Area ◽  
Financial Decision Making ◽  
Intelligent Decision Support Systems ◽  
Financial Decision

Financial decision-making is one of the most current issues of modern financial management. Financial decision-making is an area where decision support systems, knowledge-based decision support systems, and intelligent decision support systems are successfully applied. In consequence of the importance and complexity of this problem area a large number of methods of support to financial decisionmaking was developed. This paper presents the most important features of two decision support systems, a classical system and a system based on fuzzy logic. The performances of these two models are compared and the advantages achieved through the introduction of fuzzy concepts into the classical decision support systems are determined.

Assigning Value to Clinical Information – A Major Limiting Factor in the Implementation of Decision-Support Systems

1996 ◽  
Vol 35 (01) ◽  
pp. 1-4 ◽  
Author(s):  
F. T. de Dombal
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Clinical Information ◽  
Limiting Factor ◽  
Major Difficulty ◽  
Computer Aided ◽  
Computer Aided Decision

AbstractThis paper deals with a major difficulty and potential limiting factor in present-day decision support - that of assigning precise value to an item (or group of items) of clinical information. Historical determinist descriptive thinking has been challenged by current concepts of uncertainty and probability, but neither view is adequate. Four equations are proposed outlining factors which affect the value of clinical information, which explain some previously puzzling observations concerning decision support. It is suggested that without accommodation of these concepts, computer-aided decision support cannot progress further, but if they can be accommodated in future programs, the implications may be profound.

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