Titlebook: Machine Learning Methods for Ecological Applications; Alan H. Fielding Book 1999 Springer Science+Business Media New York 1999 Ecology.alg

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容易生皺紋

Harass

Equation discovery with ecological applications,measured data from real world ecosystems. The model of algal growth in the Lagoon of Venice predicts correctly most of the peaks and crashes of algal concentration. The second model of phytoplankton growth in the Danish lake Glumsoe can be successfully used for long term prediction of phytoplankton concentration.

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An introduction to machine learning methods,ted by four examples: individual recognition of the corncrake from its call; individual recognition of tigers from their footprints; choosing the ‘best’ mate and predicting the location of golden eagle nest sites.

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Artificial neural networks for pattern recognition,on (multilayer perceptron), radial basis function (RBF) and learning vector quantization ANNs are described, as examples of ANNs which employ supervised learning and which are appropriate for biological identification. The Kohonen self-organising map (SOM) and ART (adaptive resonance theory) are pre

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Genetic Algorithms I,and the choice is usually heavily weighted by the familiarity of the analyst with the selected model. Genetic algorithms, which represent a class of algorithms designed to find the best solution to a given problem by using ideas from biology, especially genetics, provide an alternative approach to m

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Genetic Algorithms II,GA algorithm, and a theoretical basis for applying it to spatial predictive modelling. The stages of analysis of a particular GA application follows. The Genetic Algorithm for Rule-set Production, or GARP, is described: including preparation of the base data, species location data, development of a

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Cellular automata,nd terminology of these tools are introduced using ecological examples. A cellular automaton consists of a grid of variously shaped cells that may represent a wide range of real spatial scales. Each cell obeys a simple set of rules that allows it to interact with its immediate neighbours. The techni

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Equation discovery with ecological applications,tific disciplines using artificial data. State of the art equation discovery systems incorporate methods for discovering regularities from real life measured data and can aid the process of scientific discovery. This chapter reviews the development of equation discovery systems and their use for mod