A weighted data fusion algorithm and its application
Yanwei Zhu · Journal of Xi'an University of Science and Technology · 2005
A weighted data fusion algorithm based on Grubbs's criterion and cluster analysis has been presented. Outlying observation data are eliminated by Grubbs's criterion. After the outlying observation data were eliminated, the cluster analysis method is used to cluster the testing data and decide the weights of each class. Then the estimate of the actual value is obtained by fusing the weights and the testing data. It has been proved that this algorithm is not only simple and efficient, but also convenient for programming by computer.