Pub Date : 2021-09-24DOI: 10.1109/ICISCAE52414.2021.9590688
Weihao Zeng, Jidong Xu
A three-phase inverter is widely used in every aspect of life and production, and fault diagnosis becomes more important. In this paper, the working characteristics and process of the traditional three-phase three-wire inverter when an open-circuit fault occurs are analyzed in-depth, and the Simulink model is built to simulate it. At the same time, the M language written by MATLAB software is used to build the diagnosis model of single-phase open-circuit fault of three-phase inverter IGBT based on a PNN neural network. The first 20 harmonics of the three-phase output voltage were selected as the eigenvalues to construct the input training samples, which were trained to make them have a certain ability of fault diagnosis.
{"title":"Inverter Fault Diagnosis Based on PNN Neural Network","authors":"Weihao Zeng, Jidong Xu","doi":"10.1109/ICISCAE52414.2021.9590688","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590688","url":null,"abstract":"A three-phase inverter is widely used in every aspect of life and production, and fault diagnosis becomes more important. In this paper, the working characteristics and process of the traditional three-phase three-wire inverter when an open-circuit fault occurs are analyzed in-depth, and the Simulink model is built to simulate it. At the same time, the M language written by MATLAB software is used to build the diagnosis model of single-phase open-circuit fault of three-phase inverter IGBT based on a PNN neural network. The first 20 harmonics of the three-phase output voltage were selected as the eigenvalues to construct the input training samples, which were trained to make them have a certain ability of fault diagnosis.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131949113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-24DOI: 10.1109/ICISCAE52414.2021.9590755
Xiaocheng Gao, Yannan Mu
With the deepening of teaching reform and the development of computer technology and application, multimedia network teaching has become the development direction of traditional teaching mode. In recent years, a large number of multimedia teaching software have emerged at home and abroad, most of which have relatively similar characteristics, such as audio/video interaction, sharing the whiteboard, teaching broadcast, with specific user roles and permission control, etc. The transmission and synchronization of multimedia stream is a research hotspot in real-time multimedia system. In this paper, the transmission protocol, delay model and synchronization strategy in multimedia stream network transmission are discussed deeply, and the calculation method of static buffer size of receiver is given. A new algorithm of dynamically changing playback rate according to the change of buffer is proposed to realize multimedia synchronization. On J2EE platform, the functions of distributed and developable network teaching system based on SOA architecture are realized. According to the requirements of unified modelling language UML in software engineering, the network teaching system was modelled, and various types of model description diagrams needed by the system were completed in Rational Rose, a UML development tool. According to the requirements of software engineering, the outline design and detailed design of the network teaching system based on UML and the concrete implementation in the object-oriented development platform are completed. It greatly improves the level and work efficiency of multimedia teaching and network teaching, and provides reliable technical support and strong technical support for teachers to carry out multimedia teaching activities smoothly in network classroom.
{"title":"Interactive multimedia Network teaching evaluation based on object segmentation algorithm","authors":"Xiaocheng Gao, Yannan Mu","doi":"10.1109/ICISCAE52414.2021.9590755","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590755","url":null,"abstract":"With the deepening of teaching reform and the development of computer technology and application, multimedia network teaching has become the development direction of traditional teaching mode. In recent years, a large number of multimedia teaching software have emerged at home and abroad, most of which have relatively similar characteristics, such as audio/video interaction, sharing the whiteboard, teaching broadcast, with specific user roles and permission control, etc. The transmission and synchronization of multimedia stream is a research hotspot in real-time multimedia system. In this paper, the transmission protocol, delay model and synchronization strategy in multimedia stream network transmission are discussed deeply, and the calculation method of static buffer size of receiver is given. A new algorithm of dynamically changing playback rate according to the change of buffer is proposed to realize multimedia synchronization. On J2EE platform, the functions of distributed and developable network teaching system based on SOA architecture are realized. According to the requirements of unified modelling language UML in software engineering, the network teaching system was modelled, and various types of model description diagrams needed by the system were completed in Rational Rose, a UML development tool. According to the requirements of software engineering, the outline design and detailed design of the network teaching system based on UML and the concrete implementation in the object-oriented development platform are completed. It greatly improves the level and work efficiency of multimedia teaching and network teaching, and provides reliable technical support and strong technical support for teachers to carry out multimedia teaching activities smoothly in network classroom.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134104988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-24DOI: 10.1109/ICISCAE52414.2021.9590794
Yufei Song, M. Chu
Nowadays, in the network age, computer security issues have attracted much attention. In order to ensure computer network security, it is necessary to pay attention to improving data encryption technology. Data encryption technology is mainly divided into two types: asymmetric key and symmetric key. Generally, the sender and receiver use different password settings to realize network security. In this paper, a scheme of applying machine learning classification algorithm to homomorphic encrypted data sets is proposed: firstly, the plaintext is preprocessed to ensure that it meets the requirements of homomorphic encryption of data; Then, compare and sort the encrypted data set by protocol. Finally, the classification results are obtained. Combined with machine learning algorithm, the text information hiding convergence is controlled, and the text information hiding algorithm is optimized. Simulation results show that this method can hide text information in a higher depth, and has stronger anti-attack ability, thus improving the security of text information storage.
{"title":"Research on the Application of Data Encryption Technology in Computer Network Security Based on Machine Learning","authors":"Yufei Song, M. Chu","doi":"10.1109/ICISCAE52414.2021.9590794","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590794","url":null,"abstract":"Nowadays, in the network age, computer security issues have attracted much attention. In order to ensure computer network security, it is necessary to pay attention to improving data encryption technology. Data encryption technology is mainly divided into two types: asymmetric key and symmetric key. Generally, the sender and receiver use different password settings to realize network security. In this paper, a scheme of applying machine learning classification algorithm to homomorphic encrypted data sets is proposed: firstly, the plaintext is preprocessed to ensure that it meets the requirements of homomorphic encryption of data; Then, compare and sort the encrypted data set by protocol. Finally, the classification results are obtained. Combined with machine learning algorithm, the text information hiding convergence is controlled, and the text information hiding algorithm is optimized. Simulation results show that this method can hide text information in a higher depth, and has stronger anti-attack ability, thus improving the security of text information storage.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124661486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-24DOI: 10.1109/ICISCAE52414.2021.9590761
Chunrong Xia, Irfan Qaisar, M. S. Aslam, Lin Qiaoyu
In this article, a sliding mode control (SMC) is used to design the tracking control for the neural system based on a networked control system (NCS) that appeared with time delays. First, we established the mathematical forms for the stability analysis, and then proposed the radial basis function to approximate the nonlinear function. Second, we propose the discrete event-triggered scheme (ETS) as a way to make better use of existing bandwidth. Only when our sampled data of plant violates the specific event-triggered condition does the sensor release the data under this ETS. Finally, a nonlinear example is given to demonstrate the effectiveness of our co-design method.
{"title":"Tracking Control of Neural System using Adaptive Sliding Mode Control for Unknown Nonlinear Function","authors":"Chunrong Xia, Irfan Qaisar, M. S. Aslam, Lin Qiaoyu","doi":"10.1109/ICISCAE52414.2021.9590761","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590761","url":null,"abstract":"In this article, a sliding mode control (SMC) is used to design the tracking control for the neural system based on a networked control system (NCS) that appeared with time delays. First, we established the mathematical forms for the stability analysis, and then proposed the radial basis function to approximate the nonlinear function. Second, we propose the discrete event-triggered scheme (ETS) as a way to make better use of existing bandwidth. Only when our sampled data of plant violates the specific event-triggered condition does the sensor release the data under this ETS. Finally, a nonlinear example is given to demonstrate the effectiveness of our co-design method.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114399318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-24DOI: 10.1109/ICISCAE52414.2021.9590691
Zhiang Dong
In this paper, we propose a mixed time-asymmetric (MTA) CNN which uses time-asymmetric convolution to extract non-local temporal feature and uses normal convolution to extract local temporal features. With the fusion of local and non-local temporal feature, our MTA CNN can achieve better action recognition accuracy while keeping the network lightweight and fast. Specially, temporal feature fusion method is designed to replace the common global average pooling in our MTA CNN so as to obtain higher-dimensional feature vector and retain more information. Extensive experimental results demonstrate that our methods can achieve comparable results on Kinetics-400 and UCF101 among leading methods with less parameters and more faster recognition speed.
{"title":"Fast Action Recognition Based on Local and Nonlocal Temporal Feature","authors":"Zhiang Dong","doi":"10.1109/ICISCAE52414.2021.9590691","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590691","url":null,"abstract":"In this paper, we propose a mixed time-asymmetric (MTA) CNN which uses time-asymmetric convolution to extract non-local temporal feature and uses normal convolution to extract local temporal features. With the fusion of local and non-local temporal feature, our MTA CNN can achieve better action recognition accuracy while keeping the network lightweight and fast. Specially, temporal feature fusion method is designed to replace the common global average pooling in our MTA CNN so as to obtain higher-dimensional feature vector and retain more information. Extensive experimental results demonstrate that our methods can achieve comparable results on Kinetics-400 and UCF101 among leading methods with less parameters and more faster recognition speed.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134585253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-24DOI: 10.1109/ICISCAE52414.2021.9590694
Yancheng Long, J. Rong
Data mining in the seismic anomaly database will be affected by the instability of the seismic monitoring system signal and the environment, so in the development of practice should be based on the existing technology to comprehensively explore, pay attention to gradually break through the limitations of traditional mining methods, in order to effectively solve the problems existing in the previous data mining. Under the background of new era, the neural network as a machine learning algorithm is the most common way of mining, need according to the related theory had a clear standard equation of the minimum mean square error values, thus to build optimized mining model, and then using the calculation data of database, the feature vector to construct the corresponding to the monitoring data are accurate judgment. On the basis of understanding the current development of seismic monitoring technology, this paper proposes a new optimization model based on the constructed seismic anomaly database, and verifies its application effect in practice.
{"title":"Research on Model of Seismic Anomaly Data Mining Based on Neural Network","authors":"Yancheng Long, J. Rong","doi":"10.1109/ICISCAE52414.2021.9590694","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590694","url":null,"abstract":"Data mining in the seismic anomaly database will be affected by the instability of the seismic monitoring system signal and the environment, so in the development of practice should be based on the existing technology to comprehensively explore, pay attention to gradually break through the limitations of traditional mining methods, in order to effectively solve the problems existing in the previous data mining. Under the background of new era, the neural network as a machine learning algorithm is the most common way of mining, need according to the related theory had a clear standard equation of the minimum mean square error values, thus to build optimized mining model, and then using the calculation data of database, the feature vector to construct the corresponding to the monitoring data are accurate judgment. On the basis of understanding the current development of seismic monitoring technology, this paper proposes a new optimization model based on the constructed seismic anomaly database, and verifies its application effect in practice.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114836305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-24DOI: 10.1109/ICISCAE52414.2021.9590660
Min Wang, Sinan Wang
Internet of vehicles (IOV) is the application of internet of things technology in the intelligent transportation system, which has attracted the attention of relevant research institutions at home and abroad. By introducing the basic concept of IOV, combined with the specific application scenarios and actual characteristics of the internet of vehicles, this paper analyzes and discusses the research objectives of IOV: vehicle to vehicle, vehicle to road, vehicle to person, vehicle to equipment communication. Then, some technical problems in the development process of IOV are analyzed, and the application services that IOV can provide and the problems in the development are summarized. The technology of IOV involves many subjects and needs further research.
车联网(Internet of vehicles, IOV)是物联网技术在智能交通系统中的应用，已引起国内外相关研究机构的关注。本文通过介绍车联网的基本概念，结合车联网的具体应用场景和实际特点，对车联网的研究目标:车对车、车对路、车对人、车对设备通信进行了分析和探讨。然后，分析了车联网发展过程中存在的一些技术问题，总结了车联网能够提供的应用服务以及发展中存在的问题。车联网技术涉及众多学科，需要进一步研究。
{"title":"Communication Technology and Application in Internet of Vehicles","authors":"Min Wang, Sinan Wang","doi":"10.1109/ICISCAE52414.2021.9590660","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590660","url":null,"abstract":"Internet of vehicles (IOV) is the application of internet of things technology in the intelligent transportation system, which has attracted the attention of relevant research institutions at home and abroad. By introducing the basic concept of IOV, combined with the specific application scenarios and actual characteristics of the internet of vehicles, this paper analyzes and discusses the research objectives of IOV: vehicle to vehicle, vehicle to road, vehicle to person, vehicle to equipment communication. Then, some technical problems in the development process of IOV are analyzed, and the application services that IOV can provide and the problems in the development are summarized. The technology of IOV involves many subjects and needs further research.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117338994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-24DOI: 10.1109/ICISCAE52414.2021.9590721
Ji Liu, Yunpeng Zhao
In the past few years, collaborative AI-infused machines have been introduced as a new generation of industrial “workers”, working with humans to share the workload. These “workers” have the potential to realize Human-Machine Collaboration (HMC),which enables flexible automation. However, combining intelligent machines with humans to obtain more efficient and accuracy human-in-the-loop solutions is a nontrivial task. Therefore, how to allocate tasks between humans and machines has become an important issue in system design. Inspiring by the graph path searching, in this paper, we adopt an acyclic direction graph to construct the role-oriented task allocation problem, and develop an Ant colony optimization based Human-Machine Task Allocation (A-HMTA) approach to find an optimized allocation solution in the search space. Experimental results show that our approach is superior to traditional approaches in terms of cost and time consumption.
{"title":"Role-oriented Task Allocation in Human-Machine Collaboration System","authors":"Ji Liu, Yunpeng Zhao","doi":"10.1109/ICISCAE52414.2021.9590721","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590721","url":null,"abstract":"In the past few years, collaborative AI-infused machines have been introduced as a new generation of industrial “workers”, working with humans to share the workload. These “workers” have the potential to realize Human-Machine Collaboration (HMC),which enables flexible automation. However, combining intelligent machines with humans to obtain more efficient and accuracy human-in-the-loop solutions is a nontrivial task. Therefore, how to allocate tasks between humans and machines has become an important issue in system design. Inspiring by the graph path searching, in this paper, we adopt an acyclic direction graph to construct the role-oriented task allocation problem, and develop an Ant colony optimization based Human-Machine Task Allocation (A-HMTA) approach to find an optimized allocation solution in the search space. Experimental results show that our approach is superior to traditional approaches in terms of cost and time consumption.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116282391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-24DOI: 10.1109/ICISCAE52414.2021.9590808
Ruizhen Wu, Ping Huang, Jingjing Chen, Lin Wang, Yan Wu, Mingming Wang
Optical neural networks (ONNs) can process information in parallel and have low energy advantages which researched more and more recently aims to replace the electrical Artificial neural networks (ANN s) solutions. The MZI with Gridnet or FFTnet can realize the convolution calculation is already proved by lots of researches. But the activation functions still have to use the DAC/ ADC to do the photoelectric conversion and then calculated in electronic-based hardware systems. We proposed a discrete estimate scheme for all-optical activation function in this paper. The scheme can give different accurate results with different implementation cost.
{"title":"Tanh discrete estimate for all-opical neural network based on MZI","authors":"Ruizhen Wu, Ping Huang, Jingjing Chen, Lin Wang, Yan Wu, Mingming Wang","doi":"10.1109/ICISCAE52414.2021.9590808","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590808","url":null,"abstract":"Optical neural networks (ONNs) can process information in parallel and have low energy advantages which researched more and more recently aims to replace the electrical Artificial neural networks (ANN s) solutions. The MZI with Gridnet or FFTnet can realize the convolution calculation is already proved by lots of researches. But the activation functions still have to use the DAC/ ADC to do the photoelectric conversion and then calculated in electronic-based hardware systems. We proposed a discrete estimate scheme for all-optical activation function in this paper. The scheme can give different accurate results with different implementation cost.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128973944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-24DOI: 10.1109/ICISCAE52414.2021.9590731
Yabo Luo, Hongxi Teng
Job shop Scheduling Problem is an NP-hard combinatorial optimization problem. The research on its solving algorithm has been a hot topic, and many achievements have been made. However, due to the complexity of time and variable space in the solving process of job shop scheduling problems, teaching tools of scheduling algorithms are still lacking. To solve the problem, this paper takes a topological sorting algorithm to illustrate the design principle and solving instances of the scheduling algorithm for job shop scheduling problems. Firstly, the method of using a graph to express the correlation between operations is described. Secondly, the idea of the topological sorting algorithm for job shop scheduling is proposed, and the steps of algorithm programming are explained in detail. Thirdly, based on the case, the solving performance of the algorithm is analyzed, and the solving effect of the algorithm is expounded.
{"title":"Experimental Teaching Platform Development for Topological Sorting Algorithm Education","authors":"Yabo Luo, Hongxi Teng","doi":"10.1109/ICISCAE52414.2021.9590731","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590731","url":null,"abstract":"Job shop Scheduling Problem is an NP-hard combinatorial optimization problem. The research on its solving algorithm has been a hot topic, and many achievements have been made. However, due to the complexity of time and variable space in the solving process of job shop scheduling problems, teaching tools of scheduling algorithms are still lacking. To solve the problem, this paper takes a topological sorting algorithm to illustrate the design principle and solving instances of the scheduling algorithm for job shop scheduling problems. Firstly, the method of using a graph to express the correlation between operations is described. Secondly, the idea of the topological sorting algorithm for job shop scheduling is proposed, and the steps of algorithm programming are explained in detail. Thirdly, based on the case, the solving performance of the algorithm is analyzed, and the solving effect of the algorithm is expounded.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114676836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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