Parallel Problem Solving from Nature - PPSN III: International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature, Jerusalem, Israel, October 9 - 14, 1994. Proceedings, Volume 3
Yuval Davidor, International Conference on Evolutionary Computation, Hans-Paul Schwefel, Conference on Parallel Problem Solving from Nature, Reinhard Männer
Springer Science & Business Media, Sep 21, 1994 - Computers - 642 pages
The challenges in ecosystem science encompass a broadening and strengthening of interdisciplinary ties, the transfer of knowledge of the ecosystem across scales, and the inclusion of anthropogenic impacts and human behavior into ecosystem, landscape, and regional models. The volume addresses these points within the context of studies in major ecosystem types viewed as the building blocks of central European landscapes. The research is evaluated to increase the understanding of the processes in order to unite ecosystem science with resource management. The comparison embraces coastal lowland forests, associated wetlands and lakes, agricultural land use, and montane and alpine forests. Techniques for upscaling focus on process modelling at stand and landscape scales and the use of remote sensing for landscape-level model parameterization and testing. The case studies demonstrate ways for ecosystem scientists, managers, and social scientists to cooperate.
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adaptation alleles application approach architecture Artificial average behavior bias cell chromosome classifier systems complex Conference on Genetic connections constraints convergence correlation crossover operator defined described distribution domain edge evolution strategies evolutionary algorithms Evolutionary Computation evolved example experiments Figure fitness function fitness landscape function evaluations fuzzy gene Genetic Algorithms genetic operators Genetic Programming genotype global optimum graph heuristic hillclimbers hybrid implementation improvement individual step-sizes initial population input interaction International Conference iterations L-system length Machine Learning matrix method Morgan Kaufmann multi-chip module mutation mutation operator neural networks nodes number of parents objective function offspring optimization problems output paper parameters parse tree patterns performance phenotype probability Proc Proceedings processors random randomly recombination representation rules runs scheme Schwefel search space selection simple Simulated Annealing solution step string structure Table task tion uniform crossover variables vector weights