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  • Proceedings of the 2nd International Conference on Intelligent Optimization and Big Data Management (IOBDM2025)

    Proceedings of the 2nd International Conference on Intelligent Optimization and Big Data Management (IOBDM2025) by Auer, Michael E.; Yue, Xiaoguang;

    Series: Lecture Notes in Networks and Systems;

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      • Publisher's listprice EUR 235.39
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

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    Product details:

    • Publisher Springer Nature Switzerland
    • Date of Publication 6 January 2026

    • ISBN 9783032103994
    • Binding Paperback
    • No. of pages644 pages
    • Size 235x155 mm
    • Language English
    • Illustrations XII, 644 p. 150 illus., 75 illus. in color.
    • 700

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    Long description:

    This book provides the proceedings of the 2nd International Conference on Intelligent Optimization and Big Data Management (IOBDM2025), which was held in Wuhan, China, from June 26 to 28, 2025, and was an ideal platform for presenting and discussing current trends in the field of intelligent optimization and big data management.
    Currently, the field of intelligent optimization and big data management is undergoing rapid development and transformation, with the integrated application of related new technologies becoming the focus of industry attention. To promote the progress of this field, academia and industry need to build an efficient communication platform to share cutting-edge achievements and practical experiences. The ways of research and application have changed, including the extensive use of advanced technical means such as intelligent algorithms and big data analysis.
    In addition, the continuous emergence of various emerging technologies is currently challenging traditional data management and optimization models. Effective practices in intelligent optimization and big data management need to be based on solid theories and rich industry application cases.
    As an annual conference of the International Engineering and Technology Institute (IETI) and CTI, the IOBDM conference is dedicated to exploring the basic theories, application achievements and practical experiences in the fields of intelligent optimization, computer science, information technology, big data management, and other related new technologies. Nowadays, the IOBDM conference has become an important forum for gathering global experts and scholars to exchange cutting-edge trends, research results and show practical experiences in related fields. In this way, we strive to promote the close integration between theoretical research and practical application.
    Interested readership includes policy makers in the field of data governance, academics specializing in intelligent optimization and big data, researchers in computer science and information technology, industry professionals engaged in data management, engineers focusing on intelligent algorithm development, practitioners in the big data industry, and lecturers in higher education institutions offering related disciplines, etc.

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    Table of Contents:

    Research of Stratified Teaching’s effects in Junior Schools based on DID model.- Research on the Integration of Ancient Chinese Word Segmentation and Labeling Based on CRF.- Machine Learning-Based Optimization of Neutral Equilibrium Mechanisms for Bridge Displacement Control.- An Adaptive Dual-Population PSO for Constrained Optimization Application to A Realistic Irregular Flight Recovery.- Research on the Standardized Application of the Entire Process of Digital Service Trade Supported by Internet of Things Technology.- ESG Optimization through Digital Finance Evidence from Chinese A-Share Companies.- Intelligent Optimization of Social Entrepreneurship Education A Big Data Driven Analysis of Student Satisfaction Patterns in China's Yangtze River Delta.- Research on Influencing Factors of AI in Hotel Room Service on Customer Experience Based on Multiple Linear Regression Model.

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