Improving the swimming route optimization algorithm based on big data cloud computing and directional distance sequence processing

As the times become more and more informational, people's physical fitness is gradually decreasing, and many people can't even swim through a small pond. This is very fatal for people going out and encountering sudden falls. This paper aims to study the improvement of the swimming path selection algorithm based on big data cloud computing and sequential direction distance processing.This paper adopts experimental comparison method and experimental analysis method, using big data technology, optimizes and improves the swimming route based on the idea of directional distance sequential processing, and builds a Mamdani-type fuzzy system to quickly introduce the final result. The experimental results in this article show that the efficiency of the algorithm optimized from the direction alone or from the distance is far better than the sequential processing optimization of the first direction and then the distance. The efficiency of the direction and distance sequential processing is about 1/3 higher than the efficiency of the direction optimization, but It is about 3 times more efficient than optimizing the distance! For an algorithm, this improvement is very exaggerated. The improvement of the swimming route optimization algorithm based on big data cloud computing and direction and distance order processing will have important social significance.