How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a ared threada ties the book together, weaving a tapestry that pictures the anaturala data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.Does that make humanity the pinnacle of the optimization problem? Why do guppies evolve to have different characteristics in dissimilar environments? Can the process of evolution be codified to understand these issues better?
|Title||:||Artificial Intelligence Methods in the Environmental Sciences|
|Author||:||Sue Ellen Haupt, Antonello Pasini, Caren Marzban|
|Publisher||:||Springer Science & Business Media - 2008-11-28|