By Tanvir Islam, Prashant K. Srivastava, Manika Gupta, Xuan Zhu, Saumitra Mukherjee
Computational intelligence concepts have loved transforming into curiosity in contemporary a long time one of the earth and environmental technological know-how examine groups for his or her robust skill to unravel and comprehend numerous complicated difficulties and advance novel methods towards a sustainable earth. This e-book compiles a set of contemporary advancements and rigorous functions of computational intelligence in those disciplines. suggestions lined contain man made neural networks, aid vector machines, fuzzy common sense, decision-making algorithms, supervised and unsupervised type algorithms, probabilistic computing, hybrid equipment and morphic computing. additional themes given remedy during this quantity contain distant sensing, meteorology, atmospheric and oceanic modeling, weather swap, environmental engineering and administration, catastrophic ordinary risks, air and environmental toxins and water caliber. by way of linking computational intelligence concepts with earth and environmental technology orientated difficulties, this ebook promotes synergistic actions between scientists and technicians operating in parts akin to facts mining and computer studying. We think diversified workforce of teachers, scientists, environmentalists, meteorologists and computing specialists with a typical curiosity in computational intelligence thoughts in the earth and environmental sciences will locate this ebook to be of significant value.
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Additional info for Computational Intelligence Techniques in Earth and Environmental Sciences
Other chapters in this book offer more technical discussions on some computational intelligence techniques including those that were not reviewed in this chapter. Computational intelligence is a collection of computational models and tools, whose classification, clusterization, optimization, prediction, reasoning, and approximation capabilities have been improved incrementally and continuously. There are already many computational intelligence techniques or combinations of the techniques. It is always possible to find alternative techniques to address a specific earth and environmental problem.
Environ Manage 51:267–277 Riff MC, Alfaro T, Bonnaire X, Grandon C (2008) EA-MP: an evolutionary algorithm for a mine planning problem. In: Proceedings of IEEE congress on evolutionary computation, June 2008, pp 4011–4014 Rumelhart DE, Hinton GE, Williams RJ (1986) Learning internal representations by error propagation. In: Rumelhart DE, McClelland JL (eds) Parallel distributed processing: explorations in the microstructure of cognition, vol 1. MIT Press, Cambridge, MA, pp 318–362 Sanchez E, Shibata T and Zadeh LA (1997) Genetic algorithms and fuzzy logic systems: soft computing perspectives.
Negative selection algorithms simulate the negative selection process that occurs during the maturation of T-cells in the thymus. T-cells originate in the bone marrow, but pass on to the thymus to mature before they circulate the body in the blood and lymphatic vessels. Negative selection refers to the identification and elimination of those T-cells that may recognize and attack the self-antigens presented in the thymus. All T-cells that leave the thymus to circulate throughout the body are said to be tolerant to self.