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» Time Series Forecasting by means of Evolutionary Algorithms
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EMO
2005
Springer
194views Optimization» more  EMO 2005»
14 years 1 months ago
An EMO Algorithm Using the Hypervolume Measure as Selection Criterion
Abstract. The hypervolume measure is one of the most frequently applied measures for comparing the results of evolutionary multiobjective optimization algorithms (EMOA). The idea t...
Michael Emmerich, Nicola Beume, Boris Naujoks
ICAC
2009
IEEE
14 years 2 months ago
Applying genetic algorithms to decision making in autonomic computing systems
Increasingly, applications need to be able to self-reconfigure in response to changing requirements and environmental conditions. Autonomic computing has been proposed as a means...
Andres J. Ramirez, David B. Knoester, Betty H. C. ...
CIDM
2009
IEEE
13 years 11 months ago
Clustering-based activity classification with a wrist-worn accelerometer using basic features
Abstract-- Automatic recognition of activities using time series data collected from exercise can facilitate development of applications that motivate people to exercise more frequ...
Pekka Siirtola, Perttu Laurinen, Eija Haapalainen,...
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
13 years 11 months ago
Towards estimating nadir objective vector using evolutionary approaches
Nadir point plays an important role in multi-objective optimization because of its importance in estimating the range of objective values corresponding to desired Pareto-optimal s...
Kalyanmoy Deb, Shamik Chaudhuri, Kaisa Miettinen
GECCO
2007
Springer
168views Optimization» more  GECCO 2007»
14 years 1 months ago
Stability in the self-organized evolution of networks
The modeling and analysis of large networks of autonomous agents is an important topic with applications in many different disciplines. One way of modeling the development of such...
Thomas Jansen, Madeleine Theile