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Decision support in non-conservative domains: generalization using neural networks

Author: Dutta, Soumitra ; Shekhar, S ; Wong, W. YINSEAD Area: Technology and Operations ManagementIn: Decision Support Systems, vol. 11, no. 5, June 1994 Language: EnglishDescription: p. 527-544.Type of document: INSEAD ArticleNote: Please ask the Library for this articleAbstract: Models in conventional decision support systems (DSSs) are best suited for problem solutions in domains with well defined/structured (mathematical) or partially defined/semi-structured (heuristic) domain models. Non-conservative/unstructured domains are those which either lack a known model or have a poorly defined domain model. Neural networks (NNs) represent an alternative modelling technique which can be useful in such domains. NNs autonomously learn the underlying domain model from examples and have the ability to generalise, i.e. use the learnt model to respond correctly to previously unseen inputs. This paper describes three different experiments to explore the use of NNs for providing decision support by generalisation in non-conservative/unstructured domains. The authors' results indicates that NNs have the potential to provide adequate decision support in non-conservative/unstructured domains
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Models in conventional decision support systems (DSSs) are best suited for problem solutions in domains with well defined/structured (mathematical) or partially defined/semi-structured (heuristic) domain models. Non-conservative/unstructured domains are those which either lack a known model or have a poorly defined domain model. Neural networks (NNs) represent an alternative modelling technique which can be useful in such domains. NNs autonomously learn the underlying domain model from examples and have the ability to generalise, i.e. use the learnt model to respond correctly to previously unseen inputs. This paper describes three different experiments to explore the use of NNs for providing decision support by generalisation in non-conservative/unstructured domains. The authors' results indicates that NNs have the potential to provide adequate decision support in non-conservative/unstructured domains

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