• Publications
  • Influence
The self-adaptive Pareto differential evolution algorithm
  • H. Abbass
  • Computer Science
  • Proceedings of the Congress on Evolutionary…
  • 12 May 2002
The Pareto differential evolution (PDE) algorithm was introduced and showed competitive results. The behavior of PDE, as in many other evolutionary multiobjective optimization (EMO) methods, variesExpand
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PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems
The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as multi-objective optimization problems (MOPs)) has attracted much attention. Being population basedExpand
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  • PDF
MBO: marriage in honey bees optimization-a Haplometrosis polygynous swarming approach
  • H. Abbass
  • Computer Science
  • Proceedings of the Congress on Evolutionary…
  • 27 May 2001
Honey-bees are one of the most well studied social insects. They exhibit many features that distinguish their use as models for intelligent behavior. These features include division of labor,Expand
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aiNet : An Artificial Immune Network for Data Analysis
INTRODUCTION...................................................................................................................................... 1 BASIC IDEAS AND RATIONALEExpand
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An evolutionary artificial neural networks approach for breast cancer diagnosis
  • H. Abbass
  • Medicine, Computer Science
  • Artif. Intell. Medicine
  • 1 July 2002
This paper presents an evolutionary artificial neural network (EANN) approach based on the pareto-differential evolution (PDE) algorithm augmented with local search for the prediction of breastExpand
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A Monogenous MBO Approach to Satisfiability
The marriage in honey–bees optimization (MBO) algorithm was recently proposed and showed good results for combinatorial optimization problems. Contrary to most of the swarm intelligence algorithmsExpand
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The Pareto Differential Evolution Algorithm
The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population basedExpand
  • 170
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  • PDF
Speeding Up Backpropagation Using Multiobjective Evolutionary Algorithms
  • H. Abbass
  • Computer Science, Medicine
  • Neural Computation
  • 1 November 2003
The use of backpropagation for training artificial neural networks (ANNs) is usually associated with a long training process. The user needs to experiment with a number of network architectures; withExpand
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Pareto neuro-evolution: constructing ensemble of neural networks using multi-objective optimization
  • H. Abbass
  • Computer Science
  • The Congress on Evolutionary Computation, . CEC…
  • 8 December 2003
In this paper, we present a comparison between two multiobjective formulations to the formation of neuro-ensembles. The first formulation splits the training set into two nonoverlapping stratifiedExpand
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