The Application of Artificial Intelligence Technology in the On-site Decision System of Sports Competitions

Huang, Yuhua

doi:10.1109/icbar55169.2021.00031

Cited by 2 publications

(1 citation statement)

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“…A perceptron is a simple linear classifier consisting of two layers of neurons, one for receiving input signals and the other for logical operations [5]. To solve the nonlinear separable problem, it is necessary to add functional layers to improve the learning capability of the model, so that a multilayer perceptron model is obtained [6]. The hidden and output layers are functional layers responsible for the accumulation, nonlinear transformation and output of the information coming from the previous layer [7].…”

Section: Multilayer Perceptron Model For Incomplete Datamentioning

confidence: 99%

Research and Analysis of Data Modeling in Economic Management Based on the Background of Artificial Intelligence Technology

Yang¹,

Mao²,

Li³

2023

Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19–21, 2023, Han

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In the face of the massive amount of data constantly generated, people hope to reveal the potential patterns of things and discover knowledge with important value. However, the existence of missing data not only increases the difficulty of data mining, but also reduces the reliability of analysis results. Rational filling of missing values has become a very important part of current data analysis and mining. In this paper, we use data modeling to fill the missing values in incomplete data, and construct a model to mine the association relationship between data attributes, with the goal of improving the model's ability to approximate the association relationship between incomplete data attributes. The research in this paper completely combines big data context modeling and economic growth for application and research, and makes a new breakthrough and analysis in a new research area and a new research direction.

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Section: Multilayer Perceptron Model For Incomplete Datamentioning

confidence: 99%