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» Nonlinear Predictive Control with a Gaussian Process Model
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MMNS
2007
105views Multimedia» more  MMNS 2007»
15 years 1 months ago
Monitoring Flow Aggregates with Controllable Accuracy
In this paper, we show the feasibility of real-time flow monitoring with controllable accuracy in today’s IP networks. Our approach is based on Netflow and A-GAP. A-GAP is a prot...
Alberto Gonzalez Prieto, Rolf Stadler
CORR
2011
Springer
219views Education» more  CORR 2011»
14 years 6 months ago
Active Markov Information-Theoretic Path Planning for Robotic Environmental Sensing
Recent research in multi-robot exploration and mapping has focused on sampling environmental fields, which are typically modeled using the Gaussian process (GP). Existing informa...
Kian Hsiang Low, John M. Dolan, Pradeep K. Khosla
BMCBI
2008
160views more  BMCBI 2008»
14 years 11 months ago
Dynamic sensitivity analysis of biological systems
Background: A mathematical model to understand, predict, control, or even design a real biological system is a central theme in systems biology. A dynamic biological system is alw...
Wu Hsiung Wu, Feng Sheng Wang, Maw Shang Chang
EOR
2007
117views more  EOR 2007»
14 years 11 months ago
Considering manufacturing cost and scheduling performance on a CNC turning machine
A well known industry application that allows controllable processing times is the manufacturing operations on CNC machines. For each turning operation as an example, there is a n...
Sinan Gurel, M. Selim Akturk
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
14 years 9 months ago
Genetic programming for quantitative stock selection
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
Ying L. Becker, Una-May O'Reilly