| Description |
1 online resource (xvii, 839 pages) : illustrations (chiefly color) |
| Series |
Lecture notes in networks and systems ; 724 |
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Lecture notes in networks and systems ; 724.
|
| Contents |
Intro -- Preface -- Organization -- Contents -- Prediction Model for Tax Assessments Using Data Mining and Machine Learning -- 1 Introduction -- 2 Literature Review and Related works -- 3 Methodology -- 3.1 Model Design and Implementation -- 3.2 Web Application Design and Implementation -- 4 Results -- 4.1 Random Forest Score Classifier -- 4.2 Confusion Matrix -- 4.3 ROC Curve -- 5 Discussion and Conclusion -- References -- A Review of Evaluation Metrics in Machine Learning Algorithms -- 1 Introduction -- 2 Related Work -- 3 Evaluation Metrics -- 4 Results and Discussion -- 5 Conclusion |
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3 The Proposed Approach -- 3.1 The Dataset Description -- 3.2 The STS Model -- 3.3 The (SAF) Model -- 3.4 Factors Impacting Student Performance -- 3.5 Input Layer (SAF) Model -- 3.6 Hidden Layer (SAF) Model -- 3.7 Output Layer (SAF) Model -- 4 Final Decision -- 5 Optimization Procedure -- 6 Results -- 7 Conclusion -- References -- Data Mining, Natural Language Processing and Sentiment Analysis in Vietnamese Stock Market -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 General -- 3.2 Data Crawling -- 3.3 Labeling System -- 4 Experiments -- 4.1 Dataset Number One -- 4.2 Dataset Number Two |
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4.3 Comments -- 5 Conclusions -- References -- Two Approaches to E-Book Content Classification -- 1 Introduction -- 2 An Initial Data and an "Image" Model -- 3 Classification Based on a Mixed Text-Formula Model -- 3.1 Data Preparation -- 3.2 Feature Extraction in a Text-Formula Model -- 4 Practical Results of Classification -- 5 Conclusions -- References -- On the Geometry of the Orbits of Killing Vector Fields -- 1 Introduction -- 2 The Geometry of Killing Vector Fields -- 3 The Classification of Geometry of Orbits -- 4 On the Compactness of the Orbits |
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5 Applications in Partial Differential Equations -- 6 Conclusion -- References -- The Classification of Vegetations Based on Share Reflectance at Spectral Bands -- 1 Introduction -- 2 Materials, Data and Methods -- 3 Results -- 3.1 Preparation Data of Share Reflection for Vegetations -- 3.2 Classification of Vegetations Based on Share Reflectance at Bands -- 4 Discussion -- 5 Conclusions -- References -- The Problem of Information Singularity in the Storage of Digital Data -- 1 Introduction -- 2 Overview of Information Singularity Issues -- 2.1 Storing and Interpreting Streaming Videos |
| Summary |
The application of artificial intelligence in networks and systems is a rapidly evolving field that has the potential to transform a wide range of industries. The refereed proceedings in this book is from the Artificial Intelligence Application in Networks and Systems session of the Computer Science Online Conference 2023 (CSOC 2023), which was held online in April 2023. The section brings together experts from different fields to present their research and discuss the latest trends and challenges. One of the key themes in this section is the development of intelligent systems that can learn, adapt, and optimize their performance in real time. Researchers are exploring how AI algorithms can be used to create autonomous networks and systems that can make decisions without human intervention. Furthermore, this section highlights the use of AI in improving network performance and efficiency. Researchers are exploring how AI algorithms can be used to optimize network routing, reduce congestion, and improve the quality of service. These efforts can help organizations save costs and improve user experience |
| Notes |
International conference proceedings |
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Includes author index |
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Print version record |
| Subject |
Artificial intelligence -- Congresses
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Software engineering -- Congresses
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Artificial intelligence
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Software engineering
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| Genre/Form |
Electronic books
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proceedings (reports)
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Conference papers and proceedings
|
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Conference papers and proceedings.
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Actes de congrès.
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| Form |
Electronic book
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| Author |
Silhavy, Radek, editor.
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Silhavy, Petr, editor.
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| ISBN |
9783031353147 |
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3031353145 |
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