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» Model selection in genetic programming
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APAQS
2000
IEEE
14 years 1 months ago
Software Quality Prediction Using Mixture Models with EM Algorithm
The use of the statistical technique of mixture model analysis as a tool for early prediction of fault-prone program modules is investigated. The Expectation-Maximum likelihood (E...
Ping Guo, Michael R. Lyu
ATAL
2010
Springer
13 years 10 months ago
Learning context conditions for BDI plan selection
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-calle...
Dhirendra Singh, Sebastian Sardiña, Lin Pad...
CEC
2005
IEEE
14 years 2 months ago
Evolving dispatching rules for solving the flexible job-shop problem
We solve the Flexible Job-Shop Problem (FJSP) by using dispatching rules discovered through Genetic Programming (GP). While Simple Priority Rules (SPR) have been widely applied in ...
Nhu Binh Ho, Joc Cing Tay
CEC
2007
IEEE
14 years 25 days ago
Evolution of classification rules for comprehensible knowledge discovery
This article, which lies within the data mining framework, proposes a method to build classifiers based on the evolution of rules. The method, named REC (Rule Evolution for Classif...
Emiliano Carreno, Guillermo Leguizamón, Nea...
COR
2004
99views more  COR 2004»
13 years 8 months ago
A lexicographically fair allocation of discrete bandwidth for multirate multicast traffics
Fair bandwidth allocation is an important issue in the multicast network to serve each multicast traffic at a fair rate commensurate with the receiver's capabilities and the ...
Chae Y. Lee, Young P. Moon, Young Joo Cho