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EC
2000
96views ECommerce» more  EC 2000»
13 years 8 months ago
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
David A. van Veldhuizen, Gary B. Lamont
BIBM
2008
IEEE
112views Bioinformatics» more  BIBM 2008»
14 years 3 months ago
Predicting Protective Linear B-Cell Epitopes Using Evolutionary Information
Mapping B-cell epitopes plays an important role in vaccine design, immunodiagnostic tests, and antibody production. Because the experimental determination of B-cell epitopes is ti...
Yasser El-Manzalawy, Drena Dobbs, Vasant Honavar
IAT
2008
IEEE
14 years 3 months ago
Competency-Based Intelligent Curriculum Sequencing: Comparing Two Evolutionary Approaches
The process of creating e-learning contents using reusable learning objects (LOs) can be broken down in two sub-processes: LOs finding and LO sequencing. Although semiautomatic to...
Luis de Marcos, Roberto Barchino, José-Javi...
CEC
2007
IEEE
14 years 3 months ago
Finding trade-off solutions close to KKT points using evolutionary multi-objective optimization
— Despite having a wide-spread applicability of evolutionary optimization procedures over the past few decades, EA researchers still face criticism about the theoretical optimali...
Kalyanmoy Deb, Rahul Tewari, Mayur Dixit, Joydeep ...
CEC
2007
IEEE
14 years 3 months ago
Evolutionary random neural ensembles based on negative correlation learning
— This paper proposes to incorporate bootstrap of data, random feature subspace and evolutionary algorithm with negative correlation learning to automatically design accurate and...
Huanhuan Chen, Xin Yao