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Link Quality Prediction Based On Gradient Boosting Machine

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目录

Chapter 1 Introduction

1.1 Research Background And Significance

1.2 Research Statement

1.3 Our Contributions

1.4 Thesis Structure

Chapter 2 Research Works

2.1 Link Quality Parameters

2.1.1 RSSI (Received Signal Strength Indicator)

2.1.2 LQI (Link Quality Indicator)

2.1.3 SNR(Signal To Noise Ratio)

2.1.4 PRR (Packet Received Rate)

2.2 Wireless Sensor Network Link Characteristics

2.2.1 Spatial Characteristics.

2.2.2 Temporal Characteristics.

2.2.3 Link Asymmetry.

2.2.4 Interference.

2.3 Comprehensive Link Quality Assessment Model

2.3.1 Link Quality Prediction Method Based On Link Characteristics

2.3.2 Statistics-Based Link Quality Prediction Method

2.3.3 Machine Learning-Based Link Quality Prediction Method

2.4 Summary of This Chapter

Chapter 3 Gradient Boosting

3.1 Boosting Machine

Important Component of Boosting

3.2 Gradient Boosting Machine

3.2.1 Friedman’s gradient boosting machine

3.2.2 Decreasing the learning rate

3.2.3 Variance reduction using subsampling

3.3 Summary of The Chapter

Chapter 4 Model Evaluation And Performance

4.1 Link Characteristics And Metrics

4.1.1 Link transmission efficiency`

4.1.2 Link volatility

4.1.3 Receive signal strength

4.1.4 Packet Received Rate Grading (PRR-g)

4.2 Preliminary Exploration

4.3 Methods And Techniques

4.3.1 Data Preprocessing

4.3.2 Data analysis

4.3.3 Feature generation

4.3.4 Model training

4.4 Summary of The Chapter

Chapter 5 Experiment And Analysis

5.1 Experimental Design

5.1.1 Hardware Platform

5.1.2 Software Platform

5.2 Experimental Scenarios

Data Preprocessing

5.3 Experimental Result and Analysis

5.4 Summary of This Chapter

Chapter 6 Conclusion and Further Work

6.1 Conclusion

6.2 Further Work

致谢

Research Publication

参考文献

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著录项

  • 作者

    Tijjani Ameena Jagamu;

  • 作者单位

    南昌航空大学;

  • 授予单位 南昌航空大学;
  • 学科 Software Engineer
  • 授予学位 硕士
  • 导师姓名 Jian Shu;
  • 年度 2020
  • 页码
  • 总页数
  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类 X85TP3;
  • 关键词

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