Evaluation Model for Capability of Enterprise Agent Coalition Based on Information Fusion and Attribute Reduction

For the issue of evaluation of capability of enterprise agent coalition, an evaluation model based on inlor^nation fusion and entropy weighting method is presented. The attribute reduction method is utilized to reduce indicators of the capability according to the theory of rough set. The new indicator system can be detemiined. Attribute reduction can also reduce the "workload and remove the redundant information, "when there are too many indicators or the indicators have strong correlation. The research complexity can be reduced and the efficiency can be improved. Entropy "weighting method is used to determine the "weights of the remaining indicators , and the importance of indicators is analyzed. The information fusion model based on nearest neighbor method is developed and utilized to evaluate the capability of multiple agent coalitions, compared to cloud evaluation model and D-S evidence method. Simulation results are reasonable and with obvious distinction. Thus they verify the effectiveness and feasibility of the model. The information fusion model can provide more scientific, rational decision support for choosing the best agent coalition, and provide innovative steps for the evaluation process of capability of agent coalitions.