Prototype selection for nearest neighbor classification: Taxonomy and empirical study
The nearest neighbor classifier is one of the most used and well-known techniques for
performing recognition tasks. It has also demonstrated itself to be one of the most useful …
performing recognition tasks. It has also demonstrated itself to be one of the most useful …
Diversity enhanced particle swarm optimization with neighborhood search
Particle Swarm Optimization (PSO) has shown an effective performance for solving variant
benchmark and real-world optimization problems. However, it suffers from premature …
benchmark and real-world optimization problems. However, it suffers from premature …
Self-adaptive learning based particle swarm optimization
Particle swarm optimization (PSO) is a population-based stochastic search technique for
solving optimization problems over continuous space, which has been proven to be efficient …
solving optimization problems over continuous space, which has been proven to be efficient …
[HTML][HTML] Survey on data science with population-based algorithms
This paper discusses the relationship between data science and population-based
algorithms, which include swarm intelligence and evolutionary algorithms. We reviewed two …
algorithms, which include swarm intelligence and evolutionary algorithms. We reviewed two …
A taxonomy and experimental study on prototype generation for nearest neighbor classification
The nearest neighbor (NN) rule is one of the most successfully used techniques to resolve
classification and pattern recognition tasks. Despite its high classification accuracy, this rule …
classification and pattern recognition tasks. Despite its high classification accuracy, this rule …
Particle swarm optimization
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Chaotic maps based on binary particle swarm optimization for feature selection
LY Chuang, CH Yang, JC Li - Applied Soft Computing, 2011 - Elsevier
Feature selection is a useful pre-processing technique for solving classification problems.
The challenge of solving the feature selection problem lies in applying evolutionary …
The challenge of solving the feature selection problem lies in applying evolutionary …
Bio-inspired algorithms for autonomous deployment and localization of sensor nodes
RV Kulkarni… - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
Optimal deployment and accurate localization of sensor nodes have a strong influence on
the performance of a wireless sensor network (WSN). This paper considers real-time …
the performance of a wireless sensor network (WSN). This paper considers real-time …
[HTML][HTML] Stochastic triad topology based particle swarm optimization for global numerical optimization
Particle swarm optimization (PSO) has exhibited well-known feasibility in problem
optimization. However, its optimization performance still encounters challenges when …
optimization. However, its optimization performance still encounters challenges when …
BBO-BPNN and AMPSO-BPNN for multiple-criteria inventory classification
L Cui, Y Tao, J Deng, X Liu, D Xu, G Tang - Expert Systems with …, 2021 - Elsevier
Item classification is an issue among inventory managers who want to achieve key-point
management of items with different emphases, thus prompting managers and researchers to …
management of items with different emphases, thus prompting managers and researchers to …