Computational Intelligence Techniques in Earth and Environmental Sciences [Hardcover]

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.Chapter 1: Computational intelligence techniques and applications.- Chapter 2:?Vector Autoregression (VAR) Modeling and Forecasting on Temperature, Humidity and Cloud Coverage.- Chapter 3: Exploring the Behavior and Changing Trends of Rainfall and Temperature using Statistical Computing Techniques.- Chapter 4: Time Series Model Building and Forecasting on Maximum Temperature Data.- Chapter 5: GIS Visualization of Climate Change and Prediction of Human Responses. Chapter 6: Markov Chain Analysis of Weekly Rainfall Data for Predicting Agricultural Drought.- Chapter 7: Forecasting trol#-