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检索条件"任意字段=5th IEEE International Conference on Big Data Intelligence and Computing, DataCom 2019"

共 601 条记录，以下是41-50 订阅

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Industrial Cyber Intelligent Control Operating System that Hybrid with IEC 61499 and big data on Edge computing 5

Industrial Cyber Intelligent Control Operating System that H...

引用

5th ieee international conference on Artificial intelligence and big data, ICAIBD 2022

作者： Su, Weibin MacHica, Ivy Kim Xu, Gang He, Zhengfang Kong, Yanchun University of Southeastern Philippines College of Information and Computing Davao Philippines Yunnan Technology and Business University Edge Computing Network Center Kunming China Faculty of Construction Engineering Kunming Metallurgy College Kunming China

ISBN: (纸本)9781665499132

IEC 61499 and big data systems, which are also distributed architecture, but they belong to two independent and unrelated platforms due to different network and control concepts. With the development of intelligent manufacturing factories, the big data generated by the process of industrial production is facing unprecedented challenges of storage and data processing. the current approach is to put industrial big data on cloud computing and the industrial automation control program on the side that is close to physical equipment. this architecture has the problems of low efficiency, insufficient security and poor real-time performance. the purpose of this paper is to design an architecture for intergration IEC61499 and big data. It can not only reduce the cost of building a smart factory, but also increase the security and data access velocity. More importantly, it can meet the real-time performance of industrial control. © 2022 ieee.

关键词： Edge computing

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Research on an Intelligent Structure for Push Control of Multi-Center Cloud data Pool 5

Research on an Intelligent Structure for Push Control of Mul...

引用

5th international conference on Intelligent Control, Measurement and Signal Processing, ICMSP 2023

作者： Ying, Huang Armed Police Engineering University Department of Information Engineering Xi'an710086 China

ISBN: (纸本)9798350336030

the intelligent control of complex system must first solve the problem of data calculation, application and real-time support, which is not only the difficulty and focus of control system design, but also the key to artificial intelligence and intelligent manufacturing. It is found that the essence of control system are both processing data and controlling the direction of data flow. So, the connotation of intelligence lies in an open data processing system to increase the control of data flow, thus forming the basis of real-time data processing. therefore, this paper proposes an intelligent push control structure of multi center cloud data pool. the structure takes multi-layer cloud data pool as the center, vertical cloud data pool processes global parameters, and uses block chain technology to keep data synchronization. Horizontal cloud data pool collects status data by different function, and parameters required by control loop are pushed by cloud data pool. So, cloud computing ensures the separation of data computing and control, and multi-layer cloud data pool can form sensor networks. the structure realizes the intelligent control target of complex large-scale system that can not only implement big data calculation, but also control the flow direction of data. © 2023 ieee.

关键词： Lakes

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A Complete Feature Matching Fusion Method for Palmprint Recognition 5

A Complete Feature Matching Fusion Method for Palmprint Reco...

引用

5th international conference on Robotics, Intelligent Control and Artificial intelligence, RICAI 2023

作者： Wang, Hongxia Mariano, Vladimir Y. College of Computing and Information Technologies National University Manila Philippines School of Big Data and Artificial Intelligence Anhui Xinhua University Hefei China

ISBN: (纸本)9798350357950

As we all know, the single model extraction palmprint biometric recognition information is relatively simple, and the existing traditional palmprint recognition methods are greatly affected by the external environment. In this paper, we propose a fusion method of traditional methods and deep learning, fusing at the feature layer and matching value layer respectively. the fusion strategies are maximum fusion and summation fusion. the experimental results achieve high recognition accuracy and low Equal Error Rate on both constrained environment and unrestricted environment data sets. © 2023 ieee.

关键词： Complete Feature Matching Fusion Feature-Level Fusion Palmprint Recognition

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Research on the Impact of Investor Sentiment on Chinese Wheat Futures Prices Based on Artificial intelligence Text Mining and Sentiment Analysis 5

Research on the Impact of Investor Sentiment on Chinese Whea...

引用

5th international conference on Advances in Electrical, Electronics and computing Technology, EECT 2025

作者： Wang, Yakun Li, Yongyan Huang, Zhongyang College of Digital Economics Nanning University Nanning China

ISBN: (纸本)9798331541545

In the context of today’s global economic integration, investor sentiment influences wheat futures price fluctuations through information exchange on online platforms, playing a crucial role in price discovery, risk management, and resource allocation. With the development of the internet and social media, investor sentiment has become a significant psychological factor in the market, reflected through information exchanged on online platforms, driving price fluctuations in the futures market. the purpose of this study is to explore how investor sentiment impacts wheat futures prices from the perspective of sentiment analysis, aiming to deepen the understanding of investor sentiment’s influence on financial markets and to provide market participants with big data-based sentiment insight tools to assist them in making more informed investment decisions. the analysis shows that investor sentiment is predominantly positive (59.8% positive vs. 23.6% negative), with positive sentiment significantly driving price increases, while negative sentiment has a weaker suppressive effect. Control variables like trading volume and open interest negatively impact prices, highlighting the combined influence of sentiment and trading behavior. the model demonstrates strong explanatory power (adjusted R2 = 0.632). © 2025 ieee.

关键词： Risk management

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Research on Time Series data Prediction Based on STP-GAN Algorithm 5

Research on Time Series Data Prediction Based on STP-GAN Alg...

引用

5th international conference on Robotics, Intelligent Control and Artificial intelligence, RICAI 2023

作者： Zhang, Rui Mariano, Vladimir Y. College of Computing and Information Technologies National University Manila Philippines School of Big Data and Artificial Intelligence AnHui XinHua University Hefei China

ISBN: (纸本)9798350357950

In this paper, we utilize the Sentiment Analysis technique in NLP field to provide the opinion influence factors for the algorithmic model by performing sentiment analysis on the text of the research report, introduce the GAN algorithm which is more compatible with the logic of the temporal data operation, and on the basis of which we add the Text Pathway, and put forward the text-assisted Generative Adversarial Network Prediction Model, STP-GAN. the model combines temporal data prediction with sentiment analysis to reduce the error of model training, and introduces the Transformer structure to improve the learning ability of temporal data features. In addition, STP-GAN utilizes BERT for fine-tuning and incorporates a lexicon to increase model adaptability. And on the basis of the proposed STP-GAN, the optimizer RMSPropW, which is more suitable for this research, is proposed, which uses the exponentially weighted moving average as the decay coefficient and utilizes weight decay to improve the training stability and training speed of the prediction model. © 2023 ieee.

关键词： BERT generative adversarial model optimizer sentiment propensity analysis temporal data

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Application Research of Computer Virtual Reality Technology in big data Information Face Recognition System 5

Application Research of Computer Virtual Reality Technology ...

引用

2023 5th international conference on Artificial intelligence and Computer Applications, ICAICA 2023

作者： Yu, Xin Li, Yuan Modern Finance Industry School Shandong Institute of Commerce and Technology Shandong Jinan China

ISBN: (纸本)9798350323313

this paper studies the edge-cloud collaborative face recognition technology. this project intends to integrate cloud computing technology with boundary computing technology, breaking through the limitations of traditional algorithms on network environment and expanding the scope of application of algorithms. this improves the efficiency of the user. the image feature extraction algorithm based on Resent is studied, and the ResNet34 network is perfected. By introducing the face loss function of ArcFace to guide the training of the network, the network can better understand the corner features of the face. In the boundary aspect, this project intends to study the lightweight Resent structural model based on depth-separable volume to solve the problem of limited computation and memory. the SResNet model based on the lightweight Resent structure is studied. the effectiveness and real-time performance of this method are verified by the facial recognition experiments on edge cloud collaboration. © 2023 ieee.

关键词： Face recognition

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Energy Consumption Optimization using big data Analytics for Smart Grid Management 5

Energy Consumption Optimization using Big Data Analytics for...

引用

5th international conference on Emerging Systems and Intelligent computing, ESIC 2025

作者： Devi, K. Sumithra Contractor, Dipenkumar Deepa, V. Lakshmi, T.K. Santhikala, M. Mounika, Kamati Kcg College of Technology Department of Computer Science and Engineering Chennai India Government Engineering College Department of Computer Engineering Dahod India Sri Ramakrishna College of Arts and Science Department of Information Technology Tamil Nadu Coimbatore India Malla Reddy University Department of Computer Science and Engineering Telangana Hyderabad India Ramco Institute of Technology Department of Artificial Intelligence and Data Science Tamil Nadu Rajapalayam India Mb School of Pharmaceutical Sciences Mohan Babu University Department of Pharmacy Practice Andhra Pradesh Tirupathi India

ISBN: (纸本)9798331522100

the application of big data analytics to improve energy usage efficiency in smart grids has been prompted by the rising need for power management. Adding to the above, it poses a big data solution for demand prediction, load consolidation, and fault diagnosis. Establishing the new and state-of-the-art innovative LSTM network that was employed in the forecast yielded a higher demand forecast accuracy of 94.2% compared to the previous systems. the load balancing index achieved 92% with an accuracy of 93.7% in fault detection, thus minimizing maintenance cost by 14.7% while improving grid reliability. the proposed model was found to give better results than previous conventional machine learning techniques and even modern ones which are more complex, especially for an ever-changing grid environment. Overall, these findings show the promise of big data solutions for handling the challenges of the contemporary smart grid while improving its efficiency through energy optimization. Consequently, this work lays a framework for subsequent studies on the remaining applications of advanced analytics in energy management systems. © 2025 ieee.

关键词： Smart power grids

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Development and Verification of Multi-class data in Artificial intelligence Model Group Based on Cloud computing 5

Development and Verification of Multi-class Data in Artifici...

引用

5th ieee international conference on Artificial intelligence and big data, ICAIBD 2022

作者： Xiang, Qian Sichuan Sino-Tech College of Information Technology Chengdu China

ISBN: (纸本)9781665499132

Artificial intelligence (AI) has been widely studied. Due to the increasingly wide application of multi-class data, with the characteristics of rapid arrival, rapid change, huge quantity, and potential infinity, the original classification algorithm for the static database cannot adapt to the reality of multi-class data. In order to achieve reliable and accurate data dependency analysis by loop-level parallelism detection in large programs, this paper firstly designs and implements a parallel Naive Bayes (NB) multiclass data analysis algorithm. then, we adjust the number and weight of classifiers as needed to maintain high classification accuracy and reduce the cost. Meanwhile, this paper establishes an optimal complexity model by realizing the self-organizing control of the data mining process. the results show that the parallel NB classification algorithm can bring excellent performance improvement and good scalability and can meet individuals' performance requirements for massive data classification to a certain extent. © 2022 ieee.

关键词： Cloud computing

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Research of Hybrid Collaborative Filtering Algorithm in Course Recommendation 5

Research of Hybrid Collaborative Filtering Algorithm in Cour...

引用

5th international conference on Robotics, Intelligent Control and Artificial intelligence, RICAI 2023

作者： Wang, MeiRong Mariano, Vladimir Y. College of Computing and Information Technologies National University Manila Philippines College of Big Data and Artificial Intelligence Anhui Xinhua University Hefei China

ISBN: (纸本)9798350357950

At present, as people's awareness of learning increases, more and more learning resources appear on the Internet, and online courses are becoming more and more popular. Recommendation research for online courses can help users get the quality courses they need faster. this article integrates the optimized Apriori algorithm and the user-based collaborative filtering algorithm and recommends more appropriate courses to users based on this hybrid model. the results are more reasonable than those obtained by relying on any of the above algorithms alone. © 2023 ieee.

关键词： optimized Apriori recommendation user-based collaborative filtering algorithm

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A Survey of Available Information Recovery of Binary Programs Based on Machine Learning 5

A Survey of Available Information Recovery of Binary Program...

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5th ieee international conference on Artificial intelligence and big data, ICAIBD 2022

作者： Shao, Wenqiang Yang, Qichao Guo, Xixi Cai, Ruijie State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665499132

A binary program is an executable file obtained by compiling the source code. In order to reduce the size of software or prevent reverse engineering, software publishers usually only release executable files that have stripped a lot of source information. the rich source-level information is very helpful for software hardening and malware analysis. In recent years, the rapid development of artificial intelligence has promoted the research of binary program information recovery. this paper summarizes the relevant research on effective information recovery of binary programs since 2016. Firstly, the importance of recovering source-level information from binary programs is introduced. Next, the problems are divided into three categories, compiler traceability, signature information recovery and variable information recovery of source program. Finally, based on the latest technology in this field, the future development direction is analyzed. © 2022 ieee.

关键词： Machine learning

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