Development of a short-term liquidity decision model via protocol analysis and probabilistic neural networks

Sheng Tun Li, Li Yen Shue, Weissor Shiue

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A scheme for building a decision model of short-term liquidity analysis from domain experts is presented, which combines the features of both process tracing approach and output analysis approach. The scheme consists of process tracing, output analysis, and model review component. The process tracing component applies the Concurrent Verbal Protocol Analysis to build an initial decision model by tracing through decision procedures from domain experts. The output analysis component applies Probability Neural Network to build a decision model based on the predictions of the initial model. The model review component investigates the cases where the predictions of the two models differ, and feeds the findings back to the process tracing component for further improvement. This scheme retains the explanation capability of the Protocol Analysis, and, at the same time, provides an opportunity for researchers to rectify some of the inherent problems associated with it.

Original languageEnglish
Title of host publicationProceedings of the Hawaii International Conference on System Sciences
PublisherIEEE
Number of pages1
ISBN (Print)0769504930
Publication statusPublished - 2000 Jan 1
EventThe 33rd Annual Hawaii International Conference on System Siences (HICSS-33) - Maui, USA
Duration: 2000 Jan 42000 Jan 7

Publication series

NameProceedings of the Hawaii International Conference on System Sciences
ISSN (Print)1060-3425

Other

OtherThe 33rd Annual Hawaii International Conference on System Siences (HICSS-33)
CityMaui, USA
Period00-01-0400-01-07

Fingerprint

Neural networks

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

Li, S. T., Shue, L. Y., & Shiue, W. (2000). Development of a short-term liquidity decision model via protocol analysis and probabilistic neural networks. In Proceedings of the Hawaii International Conference on System Sciences (Proceedings of the Hawaii International Conference on System Sciences). IEEE.
Li, Sheng Tun ; Shue, Li Yen ; Shiue, Weissor. / Development of a short-term liquidity decision model via protocol analysis and probabilistic neural networks. Proceedings of the Hawaii International Conference on System Sciences. IEEE, 2000. (Proceedings of the Hawaii International Conference on System Sciences).
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title = "Development of a short-term liquidity decision model via protocol analysis and probabilistic neural networks",
abstract = "A scheme for building a decision model of short-term liquidity analysis from domain experts is presented, which combines the features of both process tracing approach and output analysis approach. The scheme consists of process tracing, output analysis, and model review component. The process tracing component applies the Concurrent Verbal Protocol Analysis to build an initial decision model by tracing through decision procedures from domain experts. The output analysis component applies Probability Neural Network to build a decision model based on the predictions of the initial model. The model review component investigates the cases where the predictions of the two models differ, and feeds the findings back to the process tracing component for further improvement. This scheme retains the explanation capability of the Protocol Analysis, and, at the same time, provides an opportunity for researchers to rectify some of the inherent problems associated with it.",
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Li, ST, Shue, LY & Shiue, W 2000, Development of a short-term liquidity decision model via protocol analysis and probabilistic neural networks. in Proceedings of the Hawaii International Conference on System Sciences. Proceedings of the Hawaii International Conference on System Sciences, IEEE, The 33rd Annual Hawaii International Conference on System Siences (HICSS-33), Maui, USA, 00-01-04.

Development of a short-term liquidity decision model via protocol analysis and probabilistic neural networks. / Li, Sheng Tun; Shue, Li Yen; Shiue, Weissor.

Proceedings of the Hawaii International Conference on System Sciences. IEEE, 2000. (Proceedings of the Hawaii International Conference on System Sciences).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - A scheme for building a decision model of short-term liquidity analysis from domain experts is presented, which combines the features of both process tracing approach and output analysis approach. The scheme consists of process tracing, output analysis, and model review component. The process tracing component applies the Concurrent Verbal Protocol Analysis to build an initial decision model by tracing through decision procedures from domain experts. The output analysis component applies Probability Neural Network to build a decision model based on the predictions of the initial model. The model review component investigates the cases where the predictions of the two models differ, and feeds the findings back to the process tracing component for further improvement. This scheme retains the explanation capability of the Protocol Analysis, and, at the same time, provides an opportunity for researchers to rectify some of the inherent problems associated with it.

AB - A scheme for building a decision model of short-term liquidity analysis from domain experts is presented, which combines the features of both process tracing approach and output analysis approach. The scheme consists of process tracing, output analysis, and model review component. The process tracing component applies the Concurrent Verbal Protocol Analysis to build an initial decision model by tracing through decision procedures from domain experts. The output analysis component applies Probability Neural Network to build a decision model based on the predictions of the initial model. The model review component investigates the cases where the predictions of the two models differ, and feeds the findings back to the process tracing component for further improvement. This scheme retains the explanation capability of the Protocol Analysis, and, at the same time, provides an opportunity for researchers to rectify some of the inherent problems associated with it.

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Li ST, Shue LY, Shiue W. Development of a short-term liquidity decision model via protocol analysis and probabilistic neural networks. In Proceedings of the Hawaii International Conference on System Sciences. IEEE. 2000. (Proceedings of the Hawaii International Conference on System Sciences).