Design of Mathematical Online Training Interactive Framework based on AI-assisted Data Modeling Algorithm Visualization Process | IEEE Conference Publication | IEEE Xplore

Design of Mathematical Online Training Interactive Framework based on AI-assisted Data Modeling Algorithm Visualization Process


Abstract:

Based on the artificial intelligence algorithm, the data model of the optimal time series is researched and designed, and the data is classified by collecting and process...Show More

Abstract:

Based on the artificial intelligence algorithm, the data model of the optimal time series is researched and designed, and the data is classified by collecting and processing the time series data. A dynamic visual demonstration process is formed and applied to the design of the interactive framework for mathematical online training. The test results show that the 16 classic experimental algorithms of artificial intelligence courses included in the platform can be clearly and dynamically demonstrated, and the detailed description of the principles and steps of algorithm execution can help students deeply understand the execution process of the algorithm. The analysis of interactive behavior is intelligent, and can carry out targeted training according to the problems that arise in the learning process of students, thereby improving the learning efficiency of students.
Date of Conference: 20-22 July 2022
Date Added to IEEE Xplore: 16 August 2022
ISBN Information:

ISSN Information:

Conference Location: Nepal

I. Introduction

Artificial intelligence has received more and more attention in the computer field. And it has been applied in robots, economic and political [1] decision-making, control systems, and simulation systems. The famous Stanford University Artificial Intelligence Research Center Professor Nelson defined artificial intelligence [2] as follows: "Artificial intelligence is the discipline of knowledge - the science of how to represent knowledge and how to acquire and use knowledge." [3] Time series data themselves have very different characteristics, eg, long-term, medium-term, short-term, etc. In practical applications, models that describe short-term correlation cannot be applied to long-term correlation time series data [4].

References

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