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检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1358 条记录，以下是201-210 订阅

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Design of a community risk prevention big data platform with multiagent collaboration 2

Design of a community risk prevention big data platform with...

引用

2nd international conference on Artificial intelligence, Automation, and High-Performance computing, AIAHPC 2022

作者： Wang, Jiangtao Luo, Yaming Jia, Nan School of Informatics and Cyber Security People's Public Security University of China Beijing China Political Department Zhengzhou Customs Anti-smuggling Bureau of China Zhengzhou China

ISBN: (纸本)9781510657717

Community risk prevention is the foundation of social stability and harmony. Meanwhile, the research about community risk prevention big data platform is crucial for community safety management. On this basis, the design research of community risk prevention big data platform with multi-agent collaboration was carried out. First of all, the current situation of the construction and application of big data platform in grassroots communities in China was fully investigated, its shortcomings of poor multi-agent linkage and low intelligence degree was clarified, and the research direction of this paper was further clarified. Then, on the basis of analyzing the connotation and correlation of multi-subject community and multi-dimensional data of community risk, the functional requirements of community risk prevention platform were analyzed. Finally, the design method of multi-agent linkage big data platform for community risk prevention was proposed from the aspects of main structure, module division and design. Theoretical and methodological support for community management were provided by this study. © 2022 SPIE. All rights reserved.

关键词： big data

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Exploring Learngene via Stage-wiseWeight Sharing for Initializing Variable-sized Models 33

Exploring Learngene via Stage-wiseWeight Sharing for Initial...

引用

33rd international Joint conference on Artificial intelligence (IJCAI)

作者： Xia, Shi-Yu Zhu, Wenxuan Yang, Xu Geng, Xin Southeast Univ Sch Comp Sci & Engn Nanjing 210096 Peoples R China Southeast Univ Minist Educ Key Lab New Generat Artificial Intelligence Techn Nanjing Peoples R China

ISBN: (纸本)9781956792041

In practice, we usually need to build variable-sized models adapting for diverse resource constraints in different application scenarios, where weight initialization is an important step prior to training. The Learngene framework, introduced recently, firstly learns one compact part termed as learngene from a large well-trained model, after which learngene is expanded to initialize variable-sized models. In this paper, we start from analysing the importance of guidance for the expansion of well-trained learngene layers, inspiring the design of a simple but highly effective Learngene approach termed SWS (Stage-wise Weight Sharing), where both learngene layers and their learning process critically contribute to providing knowledge and guidance for initializing models at varying scales. Specifically, to learn learngene layers, we build an auxiliary model comprising multiple stages where the layer weights in each stage are shared, after which we train it through distillation. Subsequently, we expand these learngene layers containing stage information at their corresponding stage to initialize models of variable depths. Extensive experiments on ImageNet-1K demonstrate that SWS achieves consistent better performance compared to many models trained from scratch, while reducing around 6.6x total training costs. In some cases, SWS performs better only after 1 epoch tuning. When initializing variable-sized models adapting for different resource constraints, SWS achieves better results while reducing around 20x parameters stored to initialize these models and around 10x pre-training costs, in contrast to the pre-training and fine-tuning approach.

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Multi-Level Integration Analysis of Artificial intelligence in Computer Network Technology 6

Multi-Level Integration Analysis of Artificial Intelligence ...

引用

6th international conference on Intelligent computing and Control Systems, ICICCS 2022

作者： Xiong, Zeming Chongqing Three Gorges Vocational College School of Artificial Intelligence Chongqing404155 China

ISBN: (纸本)9781665410359

With the continuous development of science and technology, today's artificial intelligence technology has become quite mature. Artificial intelligence has many advantages. It can solve many problems in my country's computer technology and can fully reflect the role of computer network technology. Therefore, it is quite necessary to fully apply artificial intelligence technology to computer network technology. Based on the actual situation, this paper discusses the existing problems in computer technology and the application of artificial intelligence in computer network technology and multi-level fusion intervention analysis. The results show that fusion intervention analysis will increase the efficiency by 6.9%. © 2022 IEEE.

关键词： big data

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Discovering All-chain Set with Direction and Graduality Characteristics over Streaming Time Series 19

Discovering All-chain Set with Direction and Graduality Char...

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2022 IEEE SmartWorld, 19th IEEE international conference on Ubiquitous intelligence and computing, 2022 IEEE international conference on Autonomous and Trusted Vehicles conference, 22nd IEEE international conference on Scalable computing and Communications, 2022 IEEE international conference on Digital Twin, 8th IEEE international conference on Privacy computing and 2022 IEEE international conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Wang, Shaopeng Feng, Chunkai Inner Mongolia University Engineering Research Center of Ecological Big Data Ministry of Education Inner Mongolia Engineering Laboratory for Cloud Computing and Service Inner Mongolia Discipline Inspection and Supervision Big Data Laboratory Department of Software Engineering Hohhot China

ISBN: (纸本)9798350346558

Since its introduction over five years ago, time series chain has become a fundamental tool for time series analytics, finding diverse uses in dozens of domains. Recent work has generalized the definition of time series chain, and introduced a novel definition of time series chain with directionality and graduality characteristics (TSC-DG) which can significantly enhance both robustness and usability of the original time series chain. However, previous studies on TSCDG process fixed-length time series. In this work, we focus on the issue of all-chain set with direction and graduality characteristics (all-TSCS-DG) mining over streaming time series for the first time, where all-TSCS-DG is the core of current TSCDG researches. We propose an improved Naive algorithm (IN) to solve this problem. Compared to the Naive, the IN guarantees the same space costs and results firstly, secondly is the IN takes two additional optimal strategies to further improve the time efficiency. The basic ideas of these two strategies are both incremental computing. The first one can make the IN update the IB structure at each time-tick incrementally, where the IB is an important data structure that is used to obtain the all-TSCS-DG. The second one makes the IN obtain mining results at current time-tick based on the ones at the last time-tick incrementally. Extensive experiments on real dataset demonstrate the efficiency and effectiveness of the IN. © 2022 IEEE.

关键词： Time series

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Classification algorithm of streaming media big data fusion under multi-Task information filtering

Classification algorithm of streaming media big data fusion ...

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2022 international conference on Artificial intelligence, Information Processing and Cloud computing, AIIPCC 2022

作者： Ma, Miantao Chen, Zeting Fang, Zhou Xu, Haoyu Institute of Computer Control Technology Guangzhou Huali College Guangzhou China School of Media and Art Design Guangzhou Huali College Guangzhou China School of Data Science Guangzhou Huashang College Guangzhou China

ISBN: (纸本)9781665462877

In order to improve the recognition ability of streaming media big data on the communication platform of information fusion terminal, a streaming media big data fusion algorithm based on multi-Task information filtering is proposed. This paper analyzes the storage structure model of streaming media big data of information fusion terminal communication platform, uses association matching filtering fusion detection method to cluster the fusion of streaming media big data of information fusion terminal communication platform, mines fuzzy correlation feature quantity of streaming media big data of information fusion terminal communication platform, and uses support vector machine learning model to classify features of streaming media big data of information fusion terminal communication platform. According to the classification attribute of streaming media big data of information fusion terminal communication platform, multi-Task information screening and fusion clustering processing are carried out, and the feature reconstruction and optimized clustering of streaming media big data of information fusion terminal communication platform are realized by using statistical sequence analysis method. The simulation results show that this method has good adaptability in streaming media big data clustering on the communication platform of information fusion terminal, and the recognition degree of big data fusion is high and the error rate is low. © 2022 IEEE.

关键词： big data

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Machine Vision Analysis of Welding Region and its Application to Seam Tracking in Arc Welding 7

Machine Vision Analysis of Welding Region and its Applicatio...

引用

7th international conference on Cloud computing and big data Analytics, ICCCBDA 2022

作者： Fei, Xiaoyang Tan, Cheng Yuan, Zijun Collage of Science Virginia Tech BlacksburgVA24060 United States Collage of Engineering Tianjin University Beijing300072 China Monash University Faculty of Business and Economics ClaytonVIC3800 Australia

ISBN: (纸本)9781665487115

In the process of the rapid development of artificial intelligence, machine vision makes full use of image recognition technology. The application of image recognition technology in machine vision has become a very common technology and has been widely used. In the welding industry, machine vision is widely used in weld tracking, weld pool parameters and visual inspection of welding quality. It can improve the productivity of the industry and maximize the use value of this technology. The purpose of this study is to use machine vision method to analyze various welding processes, so as to know how much machine vision technology will improve the efficiency of the welding industry. © 2022 IEEE.

关键词： Industries Productivity Visualization Cloud computing Image recognition Welding Machine vision

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Key Technologies of System big data Oriented to Intelligent Network Applications 2

Key Technologies of System Big Data Oriented to Intelligent ...

引用

2nd IEEE international conference on Artificial intelligence in Everything, AIE 2022

作者： Deng, Chunhua Jiangxi University of Applied Science Nanchang China

ISBN: (数字)9781665474009

ISBN: (纸本)9781665474009

Due to the rapid development of intelligent networks and the substantial increase of network users, the subsequent exploding increase in the amount of information data is faced. However, such rapid growth has increased the difficulty of data processing, but it has also brought opportunities for the birth of key technologies of big data. Using the key technology of big data can process massive amounts of data in multiple fields and reduce the error rate of people in data processing. When centralized processing methods cannot satisfy large-scale data processing, distributed processing is slowly moving toward people's field of vision. Distributed computing technologies such as Hadoop and Spark are now more widely used. This paper studies the key technology of system big data for intelligent network applications, establishes a Spark data processing center to collect data, and uses big data technology to analyze data information processing problems under the intelligent network. © 2022 IEEE.

关键词： big data

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Research on urban intelligent network industry index based on entropy weight method and big data analysis

Research on urban intelligent network industry index based o...

引用

2022 international conference on data Analytics, computing and Artificial intelligence, ICDACAI 2022

作者： Shunkai, Wang Yi, Wang Hongyu, Niu Fan, Zhang China Automotive Technology & Research Center Co. Ltd. Tianjin China

ISBN: (数字)9781665454704

ISBN: (纸本)9781665454704

The development of intelligent automobile industry is of great significance for China's automobile industry to overtake in corners and make greater achievements. Based on this research background, firstly, 19 key cities with leading development of intelligent networked automobile industry in China are selected as evaluation subjects. Then, the (5+24) evaluation system indexes are built through the big data theory technology, that is, the evaluation methods of five first-level evaluation indexes and 24 second-level evaluation indexes. Thirdly, the entropy weight method combined with CRITIC method is used to calculate the weight of indicators. Finally, according to the scores and rankings of each city, the corresponding conclusions are given. © 2022 IEEE.

关键词： Automotive industry

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Deep Learning in the Context of big data: The Theoretical Basis of Undergraduate Education Reform 2nd

Deep Learning in the Context of Big Data: The Theoretical Ba...

引用

2nd EAI international conference on Application of big data, Blockchain, and Internet of Things for Education Informatization, bigIoT-EDU 2022

作者： Wei, Lianjuan Guangxi Police College Nanning530028 China

ISBN: (纸本)9783031239496

With the rapid development of new information technology such as big data, cloud computing, artificial intelligence and so on, the process from industrial society to information society has been accelerated. With the uncertainty of knowledge, the value demands of undergraduate education have changed substantially. How to promote deep learning and cultivate students’ deep learning is an important direction of current educational reform and development. Deep learning is an understanding learning with the characteristics of critical understanding, promotion of knowledge construction, and emphasis on transfer and application. It is an inevitable choice for the current undergraduate education reform to accurately understand the theoretical basis of deep learning, deeply excavate the value implication of deep learning, and devote ourselves to promoting the concrete practice of deep learning. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： big data

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Interaction Design in Residence Mode of Health and Tourism 10th

Interaction Design in Residence Mode of Health and Tourism

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10th international conference on Distributed, Ambient and Pervasive Interactions (DAPI) Held as Part of the 24th international conference on Human-Computer Interaction (HCII)

作者： Liu, Yanlin Wang, Ruichao Zhao, Tingwei Univ Jinan 336 West Rd Nan Xinzhuang Jinan Shandong Peoples R China Shandong Ruisheng Investment Co Ltd Weihai Peoples R China CDI Coll 3D Modeling & Animat Design Montreal PQ Canada

ISBN: (纸本)9783031054631;9783031054624

Under the background of the healthy country strategy, new health industries, new business forms and new models have emerged and expanded, and the big health industry has entered a golden period of rapid development. The integrated development of new technologies such as artificial intelligence, interactive design, health maintenance, tourism and elderly care, community e-commerce, cloud computing technology and big data makes human-computer interaction have a wider range of application fields and burst out new vitality. With the support of artificial intelligence technology, the big health industry, because of its strong relevance, a wide range of areas, deep fusion innovation with interaction design, culture, tourism, electricity, medical, big data, etc., makes the comprehensive service mode of interactive design + intelligent tourism + health maintenance + community e-commerce ushered in a new challenge. Relying on big data "design + service + text brigade + maintenance + intelligent terminal", with the support of government service platform, with artificial intelligence, integration of community electricity resources, efforts to build to "human-computer interaction, kang, brigade service and health records management" as the center, intelligent health country service network, more effectively provide more support and services for the society.

关键词： Health country Interactive design Community e-commerce Health care Artificial intelligence

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