Computational Intelligence Techniques in Earth and Environmental Sciences

1. Front Matter

   Pages i-xv

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2. General

   1. Front Matter

      Pages 1-1

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   2. Computational Intelligence Techniques and Applications

      • Xuan Zhu

      Pages 3-26

3. Classical Intelligence Techniques in Earth and Environmental Sciences

   1. Front Matter

      Pages 27-27

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   2. Vector Autoregression (VAR) Modeling and Forecasting of Temperature, Humidity, and Cloud Coverage

      • Md. Abu Shahin, Md. Ayub Ali, A. B. M. Shawkat Ali

      Pages 29-51

   3. Exploring the Behavior and Changing Trends of Rainfall and Temperature Using Statistical Computing Techniques

      • Abdus Salam Azad, Md. Kamrul Hasan, M. Arif Imtiazur Rahman, Md. Mustafizur Rahman, Nashid Shahriar

      Pages 53-78

   4. Time Series Model Building and Forecasting on Maximum Temperature Data

      • Amrina Ferdous, Md. Abu Shahin, Md. Ayub Ali

      Pages 79-91

   5. GIS Visualization of Climate Change and Prediction of Human Responses

      • P. K. Nag, Priya Dutta, Varsha Chorsiya, Anjali Nag

      Pages 93-105

4. Probabilistic and Transforms Intelligence Techniques in Earth and Environmental Sciences

   1. Front Matter

      Pages 107-107

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   2. Markov Chain Analysis of Weekly Rainfall Data for Predicting Agricultural Drought

      • A. T. M. Jahangir Alam, M. Sayedur Rahman, A. H. M. Sadaat

      Pages 109-128

   3. Forecasting Tropical Cyclones in Bangladesh: A Markov Renewal Approach

      • Md. Asaduzzaman, A. H. M. Mahbub Latif

      Pages 129-140

   4. Performance of Wavelet Transform on Models in Forecasting Climatic Variables

      • Md. Jahanur Rahman, Md. Al Mehedi Hasan

      Pages 141-154

   5. Analysis of Inter-Annual Climate Variability Using Discrete Wavelet Transform

      • Md. Khademul Islam Molla, A. T. M. Jahangir Alam, Munmun Akter, A. R. Shoyeb Ahmed Siddique, M. Sayedur Rahman

      Pages 155-171

5. Hybrid Intelligence Techniques in Earth and Environmental Sciences

   1. Front Matter

      Pages 173-173

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   2. Modeling of Suspended Sediment Concentration Carried in Natural Streams Using Fuzzy Genetic Approach

      • Özgür Kişi, Halil İbrahim Fedakar

      Pages 175-196

   3. Prediction of Local Scour Depth Downstream of Bed Sills Using Soft Computing Models

      • A. Zahiri, H. Md. Azamathulla, Kh. Ghorbani

      Pages 197-208

   4. Evaluation of Wavelet-Based De-noising Approach in Hydrological Models Linked to Artificial Neural Networks

      • Vahid Nourani, Aida Hosseini Baghanam, Aida Yahyavi Rahimi, Farzad Hassan Nejad

      Pages 209-241

   5. Evaluation of Mathematical Models with Utility Index: A Case Study from Hydrology

      • Renji Remesan, Dawei Han

      Pages 243-264

6. Back Matter

   Pages 265-266

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Computational intelligence techniques have enjoyed growing interest in recent decades among the earth and environmental science research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward a sustainable earth. This book compiles a collection of recent developments and rigorous applications of computational intelligence in these disciplines. Techniques covered include artificial neural networks, support vector machines, fuzzy logic, decision-making algorithms, supervised and unsupervised classification algorithms, probabilistic computing, hybrid methods and morphic computing. Further topics given treatment in this volume include remote sensing, meteorology, atmospheric and oceanic modeling, climate change, environmental engineering and management, catastrophic natural hazards, air and environmental pollution and water quality. By linking computational intelligence techniques with earth and environmental science oriented problems, this book promotes synergistic activities among scientists and technicians working in areas such as data mining and machine learning. We believe that a diverse group of academics, scientists, environmentalists, meteorologists and computing experts with a common interest in computational intelligence techniques within the earth and environmental sciences will find this book to be of great value.

• artificial intelligence
• environmental science
• numerical modeling

“Computational Intelligence Techniques in Earth and Environmental Sciences provides a good introductory to advanced summary of computational intelligence for complex environmental problems. It provides definitions of methods and approaches, and also includes examples where they have been applied to solve complex big data problems. Readers will find that this book helps them to understand the processes involved for environmental related complex problems, which is the purpose of computational intelligence from the outset.” (Jeff Thurston, 3dvisworld.com, March, 2014)

• NOAA/NESDIS Center for Satellite Applications and Research, College Park, MD, USA, Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA, Fort Collins, USA

  Tanvir Islam

• NASA Goddard Space Flight Center, Greenbelt & ESSIC, University of Maryland College Park, MD, USA, Greenbelt, USA

  Prashant K. Srivastava

• Department of Civil Engineering, IIT Delhi, Delhi, India

  Manika Gupta

• School of Geog. and Env. Sciences, Monash University, Melbourne, Australia

  Xuan Zhu

• School of Environmental Sciences Remote Sensing, Jawaharlal Nehru University, New Delhi, India

  Saumitra Mukherjee

Dr. Tanvir Islam is working as a post-doctoral scientist with CIRA/CSU at the NOAA/NESDIS Center for Satellite Applications and Research (STAR), College Park, MD, USA. Before joining NOAA/NESDIS, he worked as a visiting scientist/research collaborator at the University of Tokyo, Japan. He finished his PhD from the Department of Civil Engineering, University of Bristol, UK. Dr. Prashant K. Srivastava worked as an assistant professor in Environmental Sciences at Sardar Patel University, Anand, Gujarat, India from June 2007 to Sep 2010. He finished his PhD under commonwealth plan in Remote Sensing from Department of Civil Engineering, University of Bristol, U.K. Currently, he is working as a research scientist for the SMAP satellite soil moisture retrieval at ESSIC/NASA Goddard Space Flight Center, Maryland, USA. Dr. Manika Gupta completed her PhD in Geo-Environmental pollution at the Department of Civil Engineering, IIT Delhi, India. Currently, she is working as a research consultant for satellite based slum area delineation. Dr. Xuan Zhu is a senior lecturer and director of the Centre for GIS at Monash University. Dr Zhu’s areas of expertise include GIS theory, techniques and applications, decision support systems for regional sustainable development and environmental decision analysis and modelling. Dr. Saumitra Mukherjee is a professor in Geology & Remote sensing, School of Environmental sciences, Jawaharlal Nehru University, New Delhi.

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