Application of fuzzy clustering algorithm in the evaluation of abandoned wind power

Wind power prediction is based on a large number of environmental data such as wind speed, wind direction, temperature and so on, the accuracy of the data has become the key to the assessment of wind power. Because of the changes in the environment and environmental uncertainty, error detection equipment and sampling equipment, resulting in pseudo data some time points in the presence of wind power assessment, deterioration of the data attributes, and affects the accuracy of prediction model .In this paper, a feature weighted fuzzy clustering algorithm is used to cluster a large number of environmental data, and the different characteristics of the clustering results are verified by experiments. Experimental results show that this method has a significant effect on the extraction of similar data samples. It also establishes the model and training model to create a good foundation, and further improve the accuracy of wind power prediction.