A Concurrent Fuzzy-Neural Network Approach for Decision Support Systems

Title: A Concurrent Fuzzy-Neural Network Approach for Decision Support Systems

Research Question: How can a concurrent fuzzy-neural network approach be used to develop a decision support system, specifically for tactical air combat situations?

Methodology: The researchers proposed a two-step approach to develop a Tactical Air Combat Decision Support System (TACDSS). First, they used a fuzzy c-means clustering algorithm to segment the decision region based on the available data. Then, they trained a neural network using the Levenberg-Marquardt algorithm to generate decision scores for each region.

Results: The experimental results demonstrated the efficiency of the proposed technique. The researchers found that the concurrent fuzzy-neural network approach was able to effectively cluster decision regions and generate optimal decision scores for the tactical air combat situations.

Implications: The research has significant implications for the field of decision support systems. The proposed approach can be applied to other decision-making scenarios where prior knowledge is limited or unavailable. It also offers a new perspective on integrating fuzzy and neural network techniques for decision support systems.

Link to Article: https://arxiv.org/abs/0405026v1 Authors: arXiv ID: 0405026v1