Fuzzy fusion approach for hospital illness tracking

In multi-target hospital illness tracking, for data fusion, data with noise as input must be sent to fusion center to be filtered, associated, combined and made final decision as output. In this paper, an efficient fuzzy fusion approach for hospital illness tracking is proposed. The proposed approach is developed based on the fuzzy clustering means algorithm, which differs from many other fuzzy logic data fusion algorithms. Performance evaluation and results using simulations are reported, and a comparison with other fuzzy logic approaches based on the results described in other reference is also shown. The efficiency of the new approach has been demonstrated by the fuzzy system performance evaluation.