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Advanced Analytics and Learning on Temporal Data

Overview of attention for book
Cover of 'Advanced Analytics and Learning on Temporal Data'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Adjustable Context-Aware Transformer
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    Chapter 2 Clustering of Time Series Based on Forecasting Performance of Global Models
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    Chapter 3 Experimental Study of Time Series Forecasting Methods for Groundwater Level Prediction
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    Chapter 4 Fast Time Series Classification with Random Symbolic Subsequences
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    Chapter 5 RESIST: Robust Transformer for Unsupervised Time Series Anomaly Detection
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    Chapter 6 Window Size Selection in Unsupervised Time Series Analytics: A Review and Benchmark
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    Chapter 7 Application of Attention Mechanism Combined with Long Short-Term Memory for Forecasting Dissolved Oxygen in Ganga River
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    Chapter 8 Data Augmentation for Time Series Classification with Deep Learning Models
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    Chapter 9 Dimension Selection Strategies for Multivariate Time Series Classification with HIVE-COTEv2.0
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    Chapter 10 EDGAR: Embedded Detection of Gunshots by AI in Real-time
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    Chapter 11 Identification of the Best Accelerometer Features and Time-Scale to Detect Disturbances in Calves
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    Chapter 12 ODIN AD: A Framework Supporting the Life-Cycle of Time Series Anomaly Detection Applications
Attention for Chapter 7: Application of Attention Mechanism Combined with Long Short-Term Memory for Forecasting Dissolved Oxygen in Ganga River
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Chapter title
Application of Attention Mechanism Combined with Long Short-Term Memory for Forecasting Dissolved Oxygen in Ganga River
Chapter number 7
Book title
Advanced Analytics and Learning on Temporal Data
Published by
Springer, Cham, January 2023
DOI 10.1007/978-3-031-24378-3_7
Book ISBNs
978-3-03-124377-6, 978-3-03-124378-3
Authors

Pant, Neha, Toshniwal, Durga, Gurjar, Bhola Ram

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 100%
Readers by discipline Count As %
Engineering 1 100%

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