A K-means Algorithm for Prediction of Children’s Attentional Cognitive Development

Background on Children’s Attentional Cognition explores the development and changes in children’s attentional and cognitive abilities as they grow. In today’s society, there are a large error rate and lack of accuracy in children’s attentional cognitive predictions, which greatly affects children’s development. The K-means algorithm in neural networks is a technique for efficiently predicting children’s attentional cognition. This article uses the K-means algorithm to create a prediction system, which greatly improves the accuracy of predicting children’s attention cognition in advance, thereby improving children’s development. Finally, through experiments, it was concluded that the K-means algorithm is simpler to operate and has higher accuracy, which can reach 97.89%.