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检索条件"丛书名=Lecture Notes on Data Engineering and Communications Technologies"

共 334 条记录，以下是71-80 订阅

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Empirical Analysis of Online Broadcast Based on TAM Model 1

引用

作者： Liu, Mengwei Gong, Feng Zhou, Jiahui Sridhar, V. School of Economics and Management Zhixing College of Hubei University Hubei Wuhan China Nitte Meenakshi Institute of Technology Bengaluru India

ISBN: (数字)9783031318603

ISBN: (纸本)9783031318597

With the development of network communication technology, China's Internet users are growing. Webcast rose in 2016 and developed rapidly. Webcast has become a research hotspot at home and abroad. Firstly, this paper analyzes the background and characteristics of webcast, establishes a new model according to TAM theory, puts forward the research hypothesis, verifies whether the hypothesis model is established through the analysis of actual survey data, and finally puts forward relevant suggestions. According to TAM theory, the thesis establishes the influencing factor model of online purchase intention of webcast users, and draws following conclusions: information quality and reviews are positively associated with users’ attitude and purchase intention;Promotional has no significant impact on users’ attitude and purchase intention;User attitude is positively associated with purchase intention. The conclusion has certain theoretical significance and practical value. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Sales

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Machine Translation Quality Evaluation Model Based on data Mining Algorithm 1

引用

作者： Liu, Lei Lu, Nan Department of Foreign Language Qiqihar Medical University Heilongjiang Qiqihar China

ISBN: (数字)9789819911578

ISBN: (纸本)9789819911561

With the development of today's society, the contact between countries is getting closer and closer. People in different countries use different languages. It is very important to enable people in different countries to solve the first communication barrier and solve the language problem. In this environment, the technology of machine translation is becoming more and more mature. Relying on machine translation, people can not only understand the literature of different countries and regions, but also help complete the basic daily work. Moreover, the efficiency of machine translation is also higher than that of manual translation, which can not only save human resources, but also speed up the work efficiency and greatly improve the speed of social development. Similarly, there is the amount of data with the improvement of technology, so it is particularly important to apply data mining algorithms to design a model that can meet the needs of machine translation and its quality evaluation in the era of big data. This paper makes some research on the machine translation quality evaluation model based on the data mining algorithm. Based on the basic attributes of the algorithm and the background significance of machine translation, the quality evaluation model is obtained through relevant experimental simulation. By analyzing the experimental data, it can be seen that the machine translation quality evaluation model can basically meet the needs. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Quality control

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Design of Public Health Incident Warning System Based on Decision Tree Model ID3 Algorithm 1

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作者： Xu, Jiaqi Emory College of Arts and Sciences Atlanta30322 United States

ISBN: (数字)9789819911578

ISBN: (纸本)9789819911561

The development of science and technology and the rapid development of economy have greatly increased the complexity and uncertainty of human society, and created a good hotbed for the occurrence of emergencies. Health emergencies, as a common emergency in all social emergencies, have a significant negative impact on citizens’ safety, health, economic development and social stability. The high mobility of social personnel and things brought about by modern convenient transportation also provides a channel for the rapid spread of public health emergencies. Therefore, the state attaches great importance to the monitoring and rapid response of public health emergencies, and the research on the emergency decision-making methods of public health emergencies is also a research hotspot of scientists around the world. We find that many of these components are difficult to quantify for public health, and are semi-structured or unstructured problems with a variety of uncertainties. In addition, there are many factors in historical data that do not have corresponding statistics, so it is difficult to conduct scientific calculation and evaluation. Therefore, it is urgent to use advanced information technology to strengthen the management of public health emergencies. Among them, data mining is an information technology with development potential in recent years. It extracts potentially useful information and knowledge from datasets that people do not know in advance. This is an extraordinary process, represented by the model of the final understanding. This technology can effectively strengthen government emergency management. The paper uses the literature research method and investigation method, using the data mining technology, analysis and test the data mining method in public health event early warning, management, analysis and evaluation, such as original ratio, neural network, decision tree, case-based argument analysis, provide new research perspective and problem solvi

关键词： data mining

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Herd Effect Analysis of Stock Market Based on Big data Intelligent Algorithm 1

引用

作者： Zhang, E. Zhang, Xu Pareek, Piyush Kumar Zhixing College of Hubei University Hubei Wuhan China Nitte Meenakshi Institute of Technology Bengaluru India

ISBN: (数字)9783031318603

ISBN: (纸本)9783031318597

The rapid development of big data has made it widely used in all aspects of production and life. Traditional stock market analysis is mainly based on technical indicators and experience summary, with strong randomness. The application of big data in the stock market makes the stock market analysis and prediction more accurate. This paper takes the herd effect analysis in the stock market as an example, uses big data intelligent algorithm to collect and sort out the big data of the stock market, and then uses the big data of the stock market for empirical analysis, and then comes to the conclusion that there is a herd effect in China’s stock market. At the same time, by comparing the effects of China’s major policies before and after, we draw a conclusion that policies have a certain impact on the herding effect of the stock market. In view of this conclusion, the paper puts forward corresponding suggestions on the problems existing in China’s stock market. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Financial markets

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Instrumentation Automation Control System Based on HSV Space and Genetic Algorithm 1

引用

作者： Yuan, Jingchao North University of China Shanxi Taiyuan China

ISBN: (数字)9783031317750

ISBN: (纸本)9783031317743

In my country's large-scale manufacturing industry, accurate measurement and ingredients are the guarantee of output and quality in industrial production, an indispensable part of energy saving, consumption reduction, and automatic process control, and an important indicator of industrial production. Rotor scales are favored by many industrial manufacturers because of their advantages of high measurement accuracy, high stability, and simple structure. The main purpose of this paper is to design and research the instrumentation automation control system based on HSV space and genetic algorithm. This paper mainly designs a rotor scale measurement control algorithm and designs the rotor scale control instrument, which effectively improves the performance of the domestic instrument and the measurement accuracy and stability of the rotor scale system. Experiments show that, compared with several other traditional meter reading recognition algorithms, the relative error of the single-pointer recognition reading algorithm designed in this paper is significantly better than other single-method recognition results. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Genetic algorithms

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Big data Technology Driven 5G Network Optimization Analysis 1

引用

作者： Zhang, Xiujie Zhang, Xiaolin Jin, Zhongwei School of Information Engineering Heilongjiang Polytechnic Heilongjiang Harbin150001 China

ISBN: (数字)9783031318603

ISBN: (纸本)9783031318597

5G is the core of a new generation of information and communication infrastructure, with higher speed, greater capacity and lower latency than 4G. The digital transformation of production infrastructure and social infrastructure based on 5G networks is enabling technologies and applications such as big data, cloud computing and the Internet of Things to move from the conceptual to the practical, from the abstract to the concrete. There is a growing recognition of the importance of big data to the development of today’s society. Big data technology and 5G communication technology as the current emerging technology, its ability to promote the development of our economy is very strong [1, 2]. Big data technology and 5G communication technology as the current emerging technology, its ability to promote the development of our economy is very strong. The integration of big data technology and 5G communication technology can effectively enhance the development of related technologies on the one hand, and the effective integration of the two can provide strong support for the development of artificial intelligence on the other hand, laying a solid foundation for the high-quality development of China. Explain the application of big data technology in improving 5G communication architecture, the problems in the development of 5G network, combine the advantages of 5G communication network and big data technology, discuss the application practice of big data technology, and analyze the significance and value of the application of big data technology [3]. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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The Synthesis Model Based on Multimodal data for Asian Giant Hornets Sighting Report Recognition 1

引用

作者： Wu, Feiyang Han, Shengqiang Song, Jinyi Xu, Xinqing Pradeep Kumar, S. Business School Shandong Normal University Shandong Jinan China Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bangalore India

ISBN: (数字)9789819908806

ISBN: (纸本)9789819908790

Asian giant hornets (Vespa mandarinia), the largest species of hornet in the world, are the predator of honeybee populations and agricultural pests. In light of the enormous damage to local ecological balance, we obtain the experienced linear regression model by multiple linear stepwise regression. Meanwhile, the government has created the helplines and a website so that it’s convenient for people to report sightings of these hornets. Aim at the problem of the classification of the Asia giant hornet accurately, the paper presents a novel ensemble model composed of image recognition and text classification. By the joint decision function, the model integrates the prediction value of the vision transform, LSTM and BP neural network to predict the hornet category finally. Specially, taking into account that complex background and small proportion of the target area in image data, the vision transform comprises accretion onto automatic pruning based on reinforcement learning. The proposed model has been trained and validated on the available data and the accuracy rate is over 88.9%. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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Artificial Intelligence Application Processing Method and System Based on Open Source Deep Learning Framework 1

引用

作者： Deng, Chunhua Ramachandra, A.C. Jiangxi University of Applied Science Jiangxi Nanchang China Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bangalore India

ISBN: (数字)9789819908806

ISBN: (纸本)9789819908790

In the field of artificial intelligence, deep learning is a very important research topic. At present, there are a large number of machine intelligence algorithms for processing and analyzing problems, solving complex data mining and other key technologies and related application requirements, as well as deep model processing methods to realize the huge knowledge value and potential commercial value and developability of massive data. And other characteristic information content. This paper mainly uses the time series analysis method and the experimental method to carry out the correlation research on the face recognition system, and compares and analyzes the open source deep learning framework to study its processing in artificial intelligence applications. Experimental results show that when the threshold is 0.74 and the side face angle is 0, the accuracy of the face recognition system is more credible. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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A Novel Association Rules Mining Based on Improved Fusion Particle Swarm Optimization Algorithm 1

引用

作者： Tan, Qing Sun, Libo School of Information Technology Luoyang Normal University Henan Luoyang China Binghamton University State University of New York Binghamton United States

ISBN: (数字)9789819908806

ISBN: (纸本)9789819908790

Association rule learning is to mine the correlation between items and objects from certain data or other information carriers, and the results can reveal the hidden association patterns in the data. This paper firstly analyzes the advantages and disadvantages of the traditional particle swarm optimization algorithm, and finds the existing problems. Aiming at these problems, this paper improves the particle swarm optimization algorithm based on the random search theory of complex groups. In this paper, the improved fusion particle swarm optimization algorithm is used in the association rule mining model, and more effective rules can be obtained. Experiments show that the improved fusion particle swarm optimization algorithm proposed in this paper is feasible and efficient in mining association rules. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Association rules

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data Science: From Research to Application 1st ed. 2020

引用

丛书名： lecture notes on data engineering and communications technologies

2020年

作者： Mahdi Bohlouli Bahram Sadeghi Bigham Zahra Narimani Mahdi Vasighi Ebrahim Ansari

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