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检索条件"任意字段=3rd International Conference on Data Stream and Mining and Processing, DSMP 2020"

共 195 条记录，以下是1-10 订阅

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Proceedings of the 2020 IEEE 3rd international conference on data stream mining and processing, dsmp 2020

Proceedings of the 2020 IEEE 3rd International Conference on...

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3rd IEEE international conference on data stream mining and processing, dsmp 2020

ISBN: (纸本)9781728132143

The proceedings contain 88 papers. The topics discussed include: information processing system for detection impurity in technical oil based on laser;hybrid machine learning system for solving fraud detection tasks;speech signal structuring method for biometric personality identification;kln: a deep neural network architecture for keypoint localization;training neural network over encrypted data;forecasting nonlinear nonstationary processes in machine learning task;the algorithmic classification trees;development of an adaptive module of the distance education system based on a hybrid neuro-fuzzy network;new approaches in the learning of complex-valued neural networks;trainable neural networks modeling for a forecasting of start-up product development;deep neo-fuzzy neural network and its accelerated learning;and two approaches to machine learning classification of time series based on recurrence plots.

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3rd international conference on data stream and mining and processing, dsmp 2020

3rd International Conference on Data Stream and Mining and P...

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3rd international conference on data stream and mining and processing, dsmp 2020

ISBN: (纸本)9783030616557

The proceedings contain 36 papers. The special focus in this conference is on data stream and mining and processing. The topics include: Comparison analysis of clustering quality criteria using inductive methods of objective clustering;assessing the investment risk of virtual it company based on machine learning;methodological support for the management of maintaining financial flows of external tourism in global risky conditions;technology for determining the residual life of metal structures under conditions of combined loading according to acoustic emission measurements;expansion of the capabilities of chromatography-mass spectrometry due to the numerical decomposition of the signal with the mutual superposition of mass spectra;statistical methods for analyzing and processing data components when recognizing visual objects in the space of key point descriptors;sewer pipe defects classification based on deep convolutional network with information-extreme error-correction decision rules;critical modes of photography: Light sensitivity and resolution;multiclass image classification explanation with the complement perturbation images;image enhancement in automatic mode by recursive mean-separate contrast stretching;the principles of organizing the search for an object in an image, tracking an object and the selection of informative features based on the visual perception of a person;method of speech signal structuring and transforming for biometric personality identification;method of improving instance segmentation for very high resolution remote sensing imagery using deep learning;computer vision system for recognizing the coordinates location and ripeness of strawberries;novel nonparametric test for homogeneity and change-point detection in data stream;software for shelter’s fire safety and comfort levels evaluation.

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The Integration of stream data Models in Modern Transportation Networks 3

The Integration of Stream Data Models in Modern Transportati...

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3rd IEEE international conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Naval, Preeti Jain, Sandeep Kumar Krishna, K. Gopala Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Electrical Engineering Jaipur India Faculty of Engineering and Technology Department of Electronics and Communication Engineering Karnataka562112 India

ISBN: (纸本)9798350343274

The study proposal proposes an innovative strategy for managing modern transport networks, with an emphasis on the coordinated use of analytics, real-time data processing, and dynamic decision-making utilizing stream data models. To create a solid infrastructure for real-time data analysis, it is required to use a diverse set of data sources, such as sensors, GPS devices, traffic cameras, and mobile application software. A strategy for reaching this goal is described below. The real-time system that integrates transportation models, artificial intelligence, and data mining is at the core of this strategy. In addition to monitoring and assessment, one of the key responsibilities of this system is to develop the transportation network. Without this framework as a foundation, the method would be worthless. This collaborative effort provides proactive traffic control, efficient route planning, and event prediction in real time. The application of machine learning in predictive analytics and traffic analysis, which together give solid traffic forecasts, prompts the creation of tactics that cut wait times and enhance productivity. Event detection algorithms are critical for ensuring commuter safety and reducing wait times in the event of an emergency. Using cloud-hosted data processing technologies, the idea manages massive amounts of real-time data. This is critical for data collection, processing, and storage methods. Finally, we believe that the development of an intelligent transportation networkone that can continually learn, adapt, and drive itselfwill result in less traffic, more safety, shorter travel times, and environmentally friendly legislation and practices. To address the ever-increasing demands placed on dynamic urban settings, it is believed that the technique developed would transform current transport networks into more responsive, user-friendly, and efficient systems. © 2023 IEEE.

关键词： Real time systems

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Wavelet analysis of S&P 500, oil prices, and economic policy uncertainty 3

Wavelet analysis of S&P 500, oil prices, and economic policy...

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3rd international conference on Computer Vision and data mining, ICCVDM 2022

作者： Shen, Yijun Lai, Zhengyi Zhao, Zhengyang Tao, Zheng Wenzhou-Kean University College of Science and Technology Wenzhou China Wenzhou-Kean University College of Business and Public Management Wenzhou China National University of Singapore Department of Statistics and Data Science Singapore Singapore

ISBN: (纸本)9781510661363

We collect a total of 1830 data from January 2020 to June 2022 and use R for data processing and wavelet analysis. Moreover, we analyze the interactions between the COVID-19 pandemic, the Russian-Ukrainian war, crude oil price, the S&P 500 and economic policy uncertainty within a time-frequency frame work. As a result that the COVID-19 pandemic and the Russian-Ukrainian war has the extraordinary effects on the three indexes and the effect of the Russian- Ukrainian war on the crude oil price and US stock price higher than on the US economic uncertainty. © COPYRIGHT SPIE.

关键词： COVID-19

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Research on Online E-business User data mining Based on Clickstream data 22

Research on Online E-business User Data Mining Based on Clic...

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3rd Asia-Pacific conference on Image processing, Electronics and Computers, IPEC 2022

作者： Zhang, Hua Wuhan Business and Trade Vocational College Wuhan430205 China

ISBN: (纸本)9781450395786

E-business involves a huge amount of data, and the emergence of data mining technology can help enterprises quickly and accurately find and obtain valuable data information from the huge amount of data. data mining is the process of discovering new association patterns by storing a large amount of data. In the environment of e-business websites, the analysis of click stream is becoming more and more valuable, which has gone far beyond the scope of click stream. Deep analysis of these data has become an effective tool for e-business websites to understand the business situation and user behavior. Based on the analysis of click stream data of e-business users, this paper analyzes the function and process of data mining in e-business, and on this basis, puts forward the application method of data mining technology based on click stream data in e-business. Enterprises should establish the concept of keeping pace with the times and constantly strengthen the application of data mining technology to ensure that the e-business industry can develop in a positive, stable, healthy and sustainable direction. © 2022 Association for Computing Machinery. All rights reserved.

关键词： data mining

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Spark structured streaming: Customizing kafka stream processing 3

Spark structured streaming: Customizing kafka stream process...

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3rd IEEE international conference on data stream mining and processing, dsmp 2020

作者： Drohobytskiy, Yuriy Brevus, Vitaly Skorenkyy, Yuriy Pedagogical University Ternopil Volodymyr Hnatyuk National Ternopil Ukraine Dataengi UAB Vilnius Lithuania Ternopil Ivan Puluj National Technical University Ternopil Ukraine

ISBN: (纸本)9781728132143

The aim of the present paper is to develop an improvement of large-scale multi-party data exchange and stream processing solution. The method of choice uses Apache Kafka streams as well as HDFS file granulation, and is exemplified in a real project of data ingestion into the Hadoop ecosystem. The management and conditional stream controlling procedures are proposed. Various ways to manage Kafka offsets during stream processing are considered. © 2020 IEEE.

关键词： Granulation

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Foundation Models for mining 5.0: Challenges, Frameworks, and Opportunities 3

Foundation Models for Mining 5.0: Challenges, Frameworks, an...

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3rd IEEE international conference on Digital Twins and Parallel Intelligence, DTPI 2023

作者： Li, Yuchen Teng, Siyu Li, Lingxi Xuanyuan, Zhe Chen, Long Irads BNU-HKBU Uic &hkbu &waytous Zhuhai China Indiana University-Purdue University Indianapolis IndianapolisIN United States Laboratory Irads BNU-HKBU Uic Guangdong Provincial Key Zhuhai China Chinese Academy of Sciences Waytous Institute of Automation Beijing China

ISBN: (纸本)9798350318470

In recent years, there has been a widespread interest in autonomous driving, with researchers primarily focusing on issues such as edge computing, constrained scenarios, and model generalization. ChatGPT is a large-scale natural language model based on the Generative Pre-trained Transformer algorithm. It has gained popularity worldwide and is commonly referred to as a "large model"or "foundation model"due to its high parameter count (over 100M). These models possess human-like understanding capabilities, enabling them to address complex challenges through self-learning and unifying multiple subtasks. While these models are primarily designed for natural language processing (NLP) tasks, their effectiveness has also been proven in the visual and multi-modal domains. Therefore, foundation models hold promise for contributing to the development of autonomous driving technology. Autonomous driving in mining areas is considered an edge scenario, and the reliable capabilities of foundation models make them highly beneficial in such complex and harsh working environments. This article aims to explore the characteristics of mining areas, the features of foundation models, as well as the framework and key technologies related to large models in mining. It provides technical guidance for the implementation of next-generation (mining 5.0) foundation models in unmanned mines. © 2023 IEEE.

关键词： Autonomous vehicles

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A study on license plate recognition based on convolutional neural network 3

A study on license plate recognition based on convolutional ...

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3rd international conference on Computer Vision and data mining, ICCVDM 2022

作者： Shi, Xiangui Wang, Xiaole Chen, Tao Qian, Cong Liu, Yiming School of Big Data and Artificial Intelligence Anhui Xinhua University Hefei230088 China College of Computing and Information Technologies National University Manila Philippines

ISBN: (纸本)9781510661363

With the rapid development of advanced technologies such as artificial intelligence and Internet of Things, intelligent traffic management has been widely used. License plate recognition technology is particularly important in intelligent traffic management as the unique identification of vehicles, but due to the influence of natural environment, recognition angle, image clarity, size of license plate and other factors, the traditional license plate recognition technology is less robust and difficult to accurately identify the number plate number. In this paper, we describe a license plate recognition technique implemented by constructing Convolutional Neural Networks (CNN), which is able to recognize license plate numbers more accurately and has certain significance for further research on deep learning in the field of intelligent traffic management. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Image processing

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Research Analysis of stream processing System Storm Based on Knowledge Map 3

Research Analysis of Stream Processing System Storm Based on...

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3rd international conference on Computer Vision, Image and Deep Learning and international conference on Computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Li, Lina Lian, Peng Zhang, Tingting Li, Nianfeng Changchun University College of Computer Science and Technology Changchun China Changchun University College of Cyber Security Changchun China

ISBN: (纸本)9781665459112

With the development of the Internet of Things and 5G technology, stream processing systems are more and more widely used, especially the open source Storm platform. A comprehensive understanding of the research status and progress of Storm is of a certain reference value for the academic and industry to carry out related work. Based on bibliometrics theory, this paper takes the citation index of CNKI (China national knowledge infrastructure) and WOS (web of science) databases from 2013 to 2021 as the data source, and the relevant literature of Storm research and application as the research object, which is visualized and analyzed by the CiteSpace software. The knowledge maps are drawn from the aspects of temporal and spatial distribution of literature, distribution of authors and institutions, keyword co-occurrence, citation frequency and keyword prominence, and the research status, research basis, research hotspots and research trends of Storm at home and abroad are analyzed. The research results can provide references for the follow-up theoretical and application research of Storm system. © 2022 IEEE.

关键词： Storms

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Design of a system for dynamic integration of weakly structured data based on mash-up technology 3

Design of a system for dynamic integration of weakly structu...

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3rd IEEE international conference on data stream mining and processing, dsmp 2020

作者： Pelekh, Irina Berko, Andrii Andrunyk, Vasyl Chyrun, Lyubomyr Dyyak, Ivan Lviv Polytechnic National University Information Systems and Networks Department Lviv Ukraine Ivan Franko National University of Lviv Programming Department Lviv Ukraine

ISBN: (纸本)9781728132143

The article describes the design of a system for dynamic integration of weakly structured data using Mash-Up technology. Functional requirements to the system of dynamic data integration based on Mash-Up technology are characterized. An algorithm for constructing an ontological model of all integral systems and an algorithm for obtaining information resources from an integral system is proposed. The architecture and principles of the Shares and Discounts Mashup dynamic integration of weakly structured data are considered. © 2020 IEEE.

关键词： data integration

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