Artificial Intelligence in Economics and Managment An Edited Proceedings on the Fourth International Workshop: AIEM4 Tel-Aviv, Israel, January 8–10, 1996
In the past decades several researchers have developed statistical models for the prediction of corporate bankruptcy, e. g. Altman (1968) and Bilderbeek (1983). A model for predicting corporate bankruptcy aims to describe the relation between bankruptcy and a number of explanatory financial ratios....
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| Format: | eBook |
| Language: | English |
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New York, NY
Springer US
1996, 1996
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| Edition: | 1st ed. 1996 |
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| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- I. Artificial Intelligence Techniques
- Using Machine Learning, Neural Networks and Statistics to Predict Corporate Bankruptcy: A Comparative Study
- Prolog Business Objects in a Three-tier Architecture
- The Effect of Training Data Set Size and the Complexity of the Separation Function on Neural Network Classification Capability: The Two-Group Case
- Imaginal Agents
- II. Financial Applications
- Financial Product Representation and Development Using a Rule-based System
- Applications of Artificial Intelligence and Cognitive Science Techniques in Banking
- III. Business Applications
- AI-supported Quality Function Deployment
- Knowledge Reuse in Mass Customization of Knowledge-Intensive Services
- Harvest Optimization of Citrus Crop Using Genetic Algorithms
- “Corpus,” an Approach to Capitalizing Company Knowledge
- IV. Economic Applications
- Fuzzy Approach in Economic Modelling of Economics of Growth
- Computer Based Analysis of an Economy in Transition to Steady State Equilibrium
- A Multistrategy Conceptual Analysis of Economic Data
- The Credible Modeling of Economic Agents with Limited Rationality
- Reasoning and A Programming Language for Simulating Economic and Business Processes with Artificially Intelligent Agents
- V. Qualitative and Cognitive Research
- Information processing, motivation and decision making
- A Practical Tool for Explanation of Quantitative Model Behavior
- Practical Application of Artificial Intelligence in Education and Training