With the improvement of living standard, People’s requirements are also improving for children’s dietary nutrition, which fully illustrates the attention of people for healthy development of children. Children’s dietary nutrition should not be solely based on advice of expert, because every child needs different dietary nutrients. In this paper, a large data computing framework MapReduce is studied, which fully considers the eating habits of children, the balance of dietary types and the interaction of food. A intelligent decision algorithm based on large data is proposed for the best children’s dietary nutritional components. The algorithm is divided into two steps, the fuzzy GK algorithm is realized by the MapReduce framework, and the main nutrients are selected effectively; these nutrients are taken as parameters and used for multivariate linear regression model, so as to realize the rational allocation of nutrients. We design the algorithm, introduce the details of the algorithm in detail, and continuously optimize relevant parameters to produce a better dietary nutrition composition scheme. In the process of experiment, we analyze the performance of decision algorithm by testing examples, and make a lot of comparisons with the existing decision analysis algorithms. After a large number of arguments, it is proved that the algorithm is effective.
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