Handbook of HydroInformatics

Handbook of HydroInformatics

Volume II: Advanced Machine Learning Techniques

1st Edition - October 1, 2022

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  • Editors: Saeid Eslamian, Faezeh Eslamian
  • Paperback ISBN: 9780128219614

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Description

Advanced Machine Learning Techniques: Volume II: Advanced Machine Learning Techniques presents both the art of designing good learning algorithms, as well as the science of analyzing an algorithm's computational and statistical properties and performance guarantees. Global contributors cover theoretical foundation topics such as computational and statistical convergence rates, minimax estimation and concentration of measure. Advanced machine learning methods such as nonparametric density estimation, nonparametric regression, and Bayesian estimation, as well as advanced frameworks such as privacy, causality and stochastic learning algorithms are also included. Other methods covered include Cloud and Cluster Computing, Data Fusion Techniques, Empirical Orthogonal Functions and Teleconnection, Internet of Things, Kernel-Based Modeling, Large Eddy Simulation, Patter Recognition, Uncertainty-Based Resiliency Evaluation, and Volume-Based Inverse Mode, making this word an interdisciplinary guide that will appeal to post graduates  interested in Computer Science, Artificial Intelligence, Mathematical Science, Applied Science, Earth and Geoscience, Geography, Civil Engineering, Engineering, Water Science, Atmospheric Science, Social Science, Environment Science, Natural Resources and Chemical Engineering.

Key Features

  • Contains contributions from the fields of data management research, climate change and resilience, insufficient data problem, and more
  • Presents applied examples and case studies in each chapter, providing the reader with real-world scenarios for comparison
  • Defines both the designing of good learning algorithms, as well as the science of analyzing an algorithm's computational and statistical properties and performance guarantees

Readership

Post graduates and above interested in Computer Science, Mathematical Science, Applied Science, Earth and Geoscience, Geography, Civil Engineering, Engineering, Water Science, Atmospheric Science, Social Science. Environment Science, Natural Resources, Chemical Engineering

Table of Contents

  • 35. Bayesian Estimation
    36. Cloud and Cluster Computing
    37. Computational and Statistical Convergence Rates
    38. Concentration of Measure
    39. Cross Validation
    40. Data Assimilation
    41. Data Fusion Techniques
    42. Deep Learning
    43. Empirical Orthogonal Functions
    44. Empirical Orthogonal Teleconnection
    45. Error Modeling
    46. GARCH Time Series Analysis
    47. Gradient-Based Optimization
    48. Internet-Based Methods
    49. Internet of Things
    50. Kernel-Based Modeling
    51. Large Eddy Simulation
    52. Markov Chain Monte Carlo Methods
    53. Minimax Estimation
    54. Model Fusion Approach
    55. Monitoring Quality Sensors
    56. Nested Reinforcement Learning
    57. Nested Stochastic Dynamic Programming
    58. Nonparametric Density estimation
    59. Nonparametric Regressions
    60. Operational Real-Time Forecasting
    61. Patter Recognition
    62. Self-Adaptive Evolutionary Extreme Learning Machine
    63. Stochastic Learning Algorithms
    64. Supercomputing Methods (Parallelization/GPU)
    65. Transient-Based Time-Frequency Analysis
    66. Uncertainty-Based Resiliency Evaluation
    67. Volume-Based Inverse Mode
    68. WebGIS

Product details

  • No. of pages: 450
  • Language: English
  • Copyright: © Elsevier 2022
  • Published: October 1, 2022
  • Imprint: Elsevier
  • Paperback ISBN: 9780128219614

About the Editors

Saeid Eslamian

Saeid Eslamian is a Full Professor of Hydrology and Water Resources Sustainability at Isfahan University of Technology in the Department of Water Engineering. His research focuses mainly on Statistical and Environmental Hydrology and Climate Change. In particular, he is working on Modeling Natural Hazards including Flood, Drought, Storm, Wind, and Pollution toward a sustainable environment. Formerly, he was a Visiting Professor at Princeton University, United States, University of ETH Zurich, Switzerland, and McGill University, Montreal, Quebec, Canada. He has contributed to more than 400 publications in journals, books, or as technical reports. He is the Founder and Chief Editor of two journals and has been the author of about 100 books and chapters. Prof. Eslamian is the editorial board member and reviewer of about 40 Web of Science (ISI) Journals.

Affiliations and Expertise

Full Professor of Hydrology and Water Resources Sustainability, Department of Water Engineering, Isfahan University of Technology, Iran

Faezeh Eslamian

Faezeh Eslamian works at McHill University in Quebec, Canada.

Affiliations and Expertise

McHill University, Quebec, Canada

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