rocorl: Transferable Reinforcement Learning-Based Robust Control for Cyber-Physical Systems With Limited Data Updates

Yoo, Gwangpyo; Yoo, Minjong; Yeom, Ikjun; Woo, Honguk

doi:10.1109/access.2020.3044945

Cited by 4 publications

(1 citation statement)

References 21 publications

(37 reference statements)

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“…Artificial intelligence in distance education networks is the key to monitoring student success. e key of the distance teaching system of artificial intelligence network is to examine the learning effect of students and give learning suggestions in time, so as to realize the intelligence between learning and teaching [10]. e system mainly includes knowledge base, student learning module, teacher training module, evaluation module, and computer interface, as well as medical equipment as shown in Figure 2.…”

Section: Systemmentioning

confidence: 99%

Computer Teaching System Based on Internet of Things and Machine Learning

Chen

Zhang

2022

Journal of Control Science and Engineering

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In order to solve the problem that the traditional computer-aided teaching system is affected by communication technology, which leads to the inability to interact between teachers and students, the author proposes a research on a computer teaching system based on the Internet of Things and machine learning. The hardware structure is designed according to the functions of each module of the system, in which the student learning module is composed of a teaching coordination agent and a number of other agents, responsible for the presentation of specific teaching materials, problem solving, knowledge sharing through a collaborative mechanism, and providing personalized teaching basis for the system. The teacher’s teaching module mainly provides students with corresponding teaching strategies according to the learning requirements and uses its own reasoning mechanism to provide intelligent guidance to the problems encountered in the teaching process; the assessment module uses assessment rules to analyze student responses, comprehensive assessment of students’ learning behaviors, attitudes, effects, and abilities. The software function is designed with SQL Server 2000 as the database server, in the case of determining the data attributes, the data online evaluation is carried out, and the distance teaching is completed by combining the network technology. The experimental results show that when the time is 20s, the teaching efficiency of the traditional system is 61%, and the teaching efficiency of the artificial intelligence system is 91%. As a result, the teaching efficiency of the system based on the Internet of Things and machine learning is high, and it can provide equipment support for students’ learning.

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Section: Systemmentioning

confidence: 99%