2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)最新文献_第3页

Stock Price Prediction using Hybrid Deep Learning Technique for Accurate Performance 利用混合深度学习技术进行股票价格预测

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) Pub Date : 2022-12-28 DOI: 10.1109/ICKECS56523.2022.10060833

S. Thangamayan, B. Kumar, U. K, M. Arun Kumar, Dharmesh Dhabliya, S. Prabu, Rajesh N

引用次数: 2

Ameliorating the Performance of LFC in Dual Area Hydro Thermal Power System with AC/DC Lines 改善交/直流双区水火发电系统LFC性能

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) Pub Date : 2022-12-28 DOI: 10.1109/ICKECS56523.2022.10060413

C. S. Kalyan, G. Rao, S. Chaithanya, B. S. Goud, Maddala Teja Kiran Kumar, B. N. Reddy

引用次数: 0

Design of Different High-Speed Data Converters using Verilog 不同高速数据转换器的Verilog设计

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) Pub Date : 2022-12-28 DOI: 10.1109/ICKECS56523.2022.10060679

Tadigiri Aruna, Y. Ravi Sekhar

引用次数: 0

Economic and Financial Data Analysis System Based on Deep Learning and Neural Network Algorithm 基于深度学习和神经网络算法的经济金融数据分析系统

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) Pub Date : 2022-12-28 DOI: 10.1109/ICKECS56523.2022.10060240

Linlin Yu

{"title":"Economic and Financial Data Analysis System Based on Deep Learning and Neural Network Algorithm","authors":"Linlin Yu","doi":"10.1109/ICKECS56523.2022.10060240","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060240","url":null,"abstract":"Deep learning and neural network methods can analyze and predict various information performance generated by financial markets. This kind of economic and financial analysis can predict and describe the trend, price, risk and other information of financial markets in a more detailed way. In order to solve the shortcomings of the existing economic and financial data analysis and research, this paper discusses the time series model function equation, convolutional neural network and economic and financial data analysis methods, and briefly discusses the test environment, data collection and indicators of the system designed in this paper. In addition, the functions of economic and financial data analysis system are designed and discussed. Finally, deep learning and neural network CNN, LSTM and RNN technologies are applied to the prediction and analysis of stock opening price, closing price, highest price and lowest price for experiments. The experimental data show that the average prediction accuracy of CNN for stock prices reaches 87.33%. The average accuracy of LSTM for stock price prediction reached 87.37%. The average prediction accuracy of RNN for stock prices reaches 97.36, which verifies that the algorithm in this paper has a good performance effect.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124890518","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}

引用次数: 0

College English Bisection Based on Intelligent Algorithm 基于智能算法的大学英语二分法

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) Pub Date : 2022-12-28 DOI: 10.1109/ICKECS56523.2022.10059933

Weiwei Zou

{"title":"College English Bisection Based on Intelligent Algorithm","authors":"Weiwei Zou","doi":"10.1109/ICKECS56523.2022.10059933","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10059933","url":null,"abstract":"College English teaching is in the process of continuous reform. College English is an indispensable part of colleges and universities, so college English teaching can not be ignored, especially in English listening and speaking. The bisection classroom teaching style was proposed by Professor Zhangxuexin of Fudan University in 2013, and it offers new insight for scholars working on classroom teaching reform in colleges and institutions. This study applies the split classroom teaching model to college English listening and speaking teaching to encourage students to actively participate in classroom learning and improve art college students' English listening and speaking ability. The research on College English dichotomy classroom teaching based on intelligent algorithm is a new generation of intelligent algorithm, which can analyze data and find out the best teaching method. It can be used to improve students' learning ability in Colleges and universities. The research team collected data on more than 10 million college students from different countries, including China. Based on these massive data, it has developed an intelligent algorithm that can help teachers optimize their teaching skills and better use their time for each student.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128575524","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}

引用次数: 0

Computer Intelligent Course Scheduling System Based on Deep Learning 基于深度学习的计算机智能排课系统

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) Pub Date : 2022-12-28 DOI: 10.1109/ICKECS56523.2022.10060177

Xuyue Ren, Chongwei Li

{"title":"Computer Intelligent Course Scheduling System Based on Deep Learning","authors":"Xuyue Ren, Chongwei Li","doi":"10.1109/ICKECS56523.2022.10060177","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060177","url":null,"abstract":"In recent years, with the continuous development of computer technology, the successful application and penetration of computer technology in all aspects of society has made people more and more aware that the problem of school class scheduling can be solved by computer technology. The purpose of this paper is to study the design of computer intelligent course scheduling system based on deep learning. First of all, regarding the general problems existing in the current intelligent course scheduling, starting from the needs of users, and on the basis of many research results in the field of intelligent course scheduling at home and abroad, a BP neural network is proposed to provide decision-making for genetic algorithms to achieve system self-adaptation method of scheduling. Secondly, carry out detailed system design, database design, scheduling, and realize the software development of all functions of the intelligent course scheduling system. Finally, the practical problems of course arrangement are tested, the quality and efficiency of course arrangement results are analyzed and evaluated, and the practicability and practicability of the system are discussed. The experimental results show that the running time and the average teacher utilization rate of the improved genetic algorithm system both reach 95%, which is higher than the GA and AGA algorithms.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128626724","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}

引用次数: 0

Online English Education Web Page Analysis System on Account of SVM+LDA 基于SVM+LDA的在线英语教育网页分析系统

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) Pub Date : 2022-12-28 DOI: 10.1109/ICKECS56523.2022.10059825

Yan Hu

{"title":"Online English Education Web Page Analysis System on Account of SVM+LDA","authors":"Yan Hu","doi":"10.1109/ICKECS56523.2022.10059825","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10059825","url":null,"abstract":"The education system is improving with the development of The Times, English education has gradually become a part of the education system, and more and more become an important part of the education cannot be abandoned. In recent years, the scale of education and training in China has been expanding year by year. At this time, English training with a wide range of distribution has become an important point faced by educational institutions. The contents of English education are diversified and the learning level is complicated, which makes the education and training work become a difficult problem. Online English websites are now facing a more serious situation, how to efficiently and quickly solve the problem of online English education websites in front of the public. In view of this situation, it is urgent to optimize and upgrade the analysis of online English education webpage. This paper studies the design of online English education web page analysis system based on SVM+LDA, expounds the function module of online English education web page analysis, and explains its operating principle. The test shows that the design of online English education web page analysis system based on SVM+LDA has high performance in the field of online English education web page analysis.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127340538","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}

引用次数: 0

Performance Evaluation of ML Techniques for Trust-Based Employee Behavioural Classification for Access Control in Organizations 基于信任的组织访问控制员工行为分类ML技术的性能评价

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) Pub Date : 2022-12-28 DOI: 10.1109/ICKECS56523.2022.10060527

Priyanka C Hiremath, Raju G T, M. P, Chaitanya Kulkarni, Vaishak Bhuvan M R

引用次数: 0

Mutual Coupling Reduction Between Two Element Antenna Using Parallel Lines with Triangular Grooves and Tapered End 采用三角形沟槽和锥形端面平行线减小两单元天线互耦

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) Pub Date : 2022-12-28 DOI: 10.1109/ICKECS56523.2022.10060771

Sreerag M, A. Pradeep

引用次数: 0

The Teaching Reform of Japanese Majors in Newly-Built Undergraduate Colleges under the Background of Big Data 大数据背景下新建本科院校日语专业教学改革

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) Pub Date : 2022-12-28 DOI: 10.1109/ICKECS56523.2022.10059776

Xiaodong Yue

{"title":"The Teaching Reform of Japanese Majors in Newly-Built Undergraduate Colleges under the Background of Big Data","authors":"Xiaodong Yue","doi":"10.1109/ICKECS56523.2022.10059776","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10059776","url":null,"abstract":"Foreign language teaching theories have been paid much attention at home and abroad. Scholars have put forward many important views on the principles, methods and contents of foreign language teaching in their respective research fields. As the number of students in colleges and universities increases year by year, the size of colleges and universities needs to grow. The country vigorously advocates the reform of teaching mode in newly-built undergraduate colleges to make up for the talent vacancy. This paper uses big data technology to analyze the teaching reform results of Japanese majors in newly-built undergraduate colleges. It takes teachers and students of Japanese majors as the research object, analyzes the results of student ratings and teacher self-evaluation, and compares the Japanese teaching models. Changes in students' Japanese performance before and after the reform. The results showed that students' oral scores improved by 17.38%, listening scores increased by 38.65%, translation scores increased by 17.97%, and writing scores increased by 17.67%, indicating that the reformed Japanese teaching has promoted the improvement of students' Japanese ability.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131961429","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}

引用次数: 0