An inductive learning algorithm in fuzzy systems
Fuzzy Sets and Systems
Learning maximal structure rules in fuzzy logic for knowledge acquisition in expert systems
Fuzzy Sets and Systems
Fuzzy Sets and Systems - Special issue on clustering and learning
Knowledge-Based Systems in Engineering
Knowledge-Based Systems in Engineering
Decision Support Systems for Operations Management and Management Science
Decision Support Systems for Operations Management and Management Science
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
A frame knowledge system for managing financial decision knowledge
Expert Systems with Applications: An International Journal
A model for the prediction of “diseases” of firms by means of fuzzy relations
Fuzzy Sets and Systems
Predicting financial activity with evolutionary fuzzy case-based reasoning
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Developing a business failure prediction model via RST, GRA and CBR
Expert Systems with Applications: An International Journal
IEEE Transactions on Fuzzy Systems
Hi-index | 12.05 |
Nowadays firms are required to reach high levels of specialisation in order to increase their competitiveness in complex markets. Knowledge management plays a fundamental role in this process as the correct implementation of strategies is determined by the information transfer and dissemination within the organisation. In this paper, a fuzzy expert system focused on increasing accuracy and quality of the knowledge for decision making is designed. A model based on fuzzy rules to simulate the behavior of the firms, is presented under the assumption of determined input parameters previously detected and an algorithm is developed to achieve the minimal structure of the model. The result is a fuzzy expert system tool, called ESROM, which gives valuable information to help managers to improve the achievement of the strategic objectives of the company. A main contribution of this work it that the system is general and can be adapted to different scenarios.