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SCIDIR_on1389614675 |
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OCoLC |
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20231120010746.0 |
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m o d |
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cr cnu---unuuu |
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230708s2023 ne ob 001 0 eng d |
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|a EBLCP
|b eng
|e rda
|c EBLCP
|d YDX
|d OPELS
|d YDX
|d OCLCO
|d OCLCF
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|a 1389484215
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|a 9780443152856
|q electronic book
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|a 0443152853
|q electronic book
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|z 9780443152849
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|z 0443152845
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|a (OCoLC)1389614675
|z (OCoLC)1389484215
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|a QE48.8
|b .B66 2023
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|a 550.0285/57
|2 23/eng/20230815
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|a Bonakdari, Hossein,
|e author.
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|a Machine Learning in Earth, Environmental and Planetary Sciences :
|b Theoretical and Practical Applications /
|c Hossein Bonakdari, Isa Ebtehaj, Joseph D. Ladouceur.
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|a Amsterdam ;
|a Cambridge, MA :
|b Elsevier,
|c [2023]
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|a 1 online resource
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Includes bibliographical references and index.
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|a Intro -- Title page -- Table of Contents -- Copyright -- Dedication -- About the authors -- Preface -- Acknowledgments -- About the cover image -- Chapter 1. Dataset preparation -- Abstract -- 1.1 The modeling process -- 1.2 Data description -- 1.3 Different types of problems -- 1.4 Summary -- Appendix 1A Supporting information -- Appendix 1A Supplementary information -- References -- Chapter 2. Preprocessing approaches -- Abstract -- 2.1 Normalization -- 2.2 Standardization -- 2.3 Data splitting -- 2.4 Cross-validation -- 2.5 Summary -- Appendix 2A Supporting information
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|a Appendix 2A Supplementary information -- References -- Chapter 3. Postprocessing approaches -- Abstract -- 3.1 Introduction -- 3.2 Quantitative tools -- 3.3 Qualitative tools -- 3.4 Summary -- Appendix 3A Supporting information -- Appendix 3A Supplementary information -- References -- Chapter 4. Non-tuned single-layer feed-forward neural network learning machine-concept -- Abstract -- 4.1 Machine learning application in applied science -- 4.2 Mathematical definition of extreme learning machine model -- 4.3 Activation function in the extreme learning machine model -- 4.4 Summary -- References
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|a Chapter 5. Non-tuned single-layer feed-forward neural network learning machine-coding and implementation -- Abstract -- 5.1 Introduction -- 5.2 Extreme learning machine implementation in the MATLAB environment -- 5.3 Extreme learning machine modeling output -- 5.4 Calculator for extreme learning machine model -- 5.5 Effect of the extreme learning machine parameters -- 5.6 The effect of hidden layer neurons on Example 5 -- 5.7 Summary -- Appendix 5.A Supporting information -- Appendix 5.A Supporting information -- References
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|a Chapter 6. Outlier-based models of the non-tuned neural network-concept -- Abstract -- 6.1 Background of extreme learning machines -- 6.2 Extreme learning machine in the presence of outliers -- 6.3 Mathematical definition of extreme learning machine-based models -- 6.4 Summary -- References -- Chapter 7. Outlier-based models of the non-tuned neural network-coding and implementation -- Abstract -- 7.1 Developed extreme learning machine-based approaches in the presence of outliers -- 7.2 Implementation of the developed extreme learning machine-based models in the MATLAB
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|a 7.3 Calculator for outlier-based extreme learning machine models -- 7.4 Evaluating the effects of user-defined parameters on the modeling results of the extreme learning machine-based models -- 7.5 Summary -- Appendix 7.A Supporting information -- References -- Chapter 8. Online sequential non-tuned neural network-concept -- Abstract -- 8.1 Introduction -- 8.2 Main architectures of the single-layer feed-forward neural network -- 8.3 Development of the sequential-based learning algorithm -- 8.4 Main drawbacks of the classical sequential-based learning algorithms
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|a 8.5 Introduction to the online sequential extreme learning machine
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|a Description based on online resource; title from digital title page (viewed on August 15, 2023).
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650 |
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|a Earth sciences
|x Data processing.
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650 |
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|a Environmental sciences
|x Data processing.
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650 |
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|a Planetary science
|x Data processing.
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650 |
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|a Machine learning.
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650 |
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6 |
|a Sciences de l'environnement
|0 (CaQQLa)201-0097373
|x Informatique.
|0 (CaQQLa)201-0380011
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650 |
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6 |
|a Plan�etologie
|0 (CaQQLa)201-0138968
|x Informatique.
|0 (CaQQLa)201-0380011
|
650 |
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6 |
|a Apprentissage automatique.
|0 (CaQQLa)201-0131435
|
650 |
|
7 |
|a Earth sciences
|x Data processing.
|2 fast
|0 (OCoLC)fst00900738
|
650 |
|
7 |
|a Machine learning.
|2 fast
|0 (OCoLC)fst01004795
|
700 |
1 |
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|a Ebtehaj, Isa,
|e author.
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700 |
1 |
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|a Ladouceur, Joseph D.,
|e author.
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776 |
0 |
8 |
|i Print version:
|a Bonakdari, Hossein
|t Machine Learning in Earth, Environmental and Planetary Sciences
|d San Diego : Elsevier,c2023
|z 9780443152849
|
856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780443152849
|z Texto completo
|