Research on Information Processing System of Sports Combination Training Model Based on Machine Learning and Neural Network
Year: 2024
Type: article
Abstract: Information processing systems in sports and training applications are backboned by artificial intelligence for non-human intervening and accurate analysis. The fitness, performance, etc. outcomes are delivered by the system through learning implications over the different inputs. However, the recommendation/ prediction outcomes are down-surged in analyzing similar information due to learning complexity and non-adaptable outcome. Therefore, the problem is resolved by fragmenting and processing the information using a similarity measure. Therefore, this method is named as Sliced-Information Processing with Analogous Learning (SIP-AL). In this method, a neural network is used for deciding the processing feature for better accuracy. In the contrary case of down-surges, the information slicing based on an analogous point is performed. This prevents the continuity between redundant and continuous data preventing errors.
Source: Quality in Sport
Authors: Songmao Yu, Lei Wang, Tianwei Li
Institution: Southwest University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405946573