Integrated Feature Selection and Parameter Optimization for Evolving Spiking Neural Networks using Quantum Inspired Particle Swarm Optimization

被引：11

作者：

Hamed, Haza Nuzly Abdull ^{[1
]}

Kasabov, Nikola ^{[1
]}

Shamsuddin, Siti Mariyam ^{[2
]}

机构：

[1] Auckland Univ Technol, KEDRI, Auckland, New Zealand

[2] Univ Teknol Malaysia, Soft Computing Res Grp, Johor Baharu, Johor, Malaysia

来源：

2009 INTERNATIONAL CONFERENCE OF SOFT COMPUTING AND PATTERN RECOGNITION | 2009年

关键词：

Evolving Spiking Neural Network; Particle Swarm; Quantum Computing; Feature Optimization; Parameter Optimization;

D O I：

10.1109/SoCPaR.2009.139

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a novel method for optimizing features and parameters in the Evolving Spiking Neural Network (ESNN) using Quantum-inspired Particle Swarm Optimization (QiPSO). This study reveals the interesting concept of QiPSO in which information is represented as binary structures. The mechanism simultaneously optimizes the ESNN parameters and relevant features using wrapper approach. A synthetic dataset is used to evaluate the performance of the proposed method. The results show that QiPSO yields promising outcomes in obtaining the best combination of ESNN parameters as well as in identifying the most relevant features.

引用

页码：695 / +

页数：2

共 50 条

[1] String Pattern Recognition Using Evolving Spiking Neural Networks and Quantum Inspired Particle Swarm Optimization
Hamed, Haza Nuzly Abdull
Kasabov, Nikola
Michlovsky, Zbynek
Shamsuddin, Siti Mariyam
[J]. NEURAL INFORMATION PROCESSING, PT 2, PROCEEDINGS, 2009, 5864 : 611 - +
[2] Integrated Feature and Parameter Optimization for an Evolving Spiking Neural Network
Schliebs, Stefan
Defoin-Platel, Michael
Kasabov, Nikola
[J]. ADVANCES IN NEURO-INFORMATION PROCESSING, PT I, 2009, 5506 : 1229 - +
[3] Feature selection using double parallel feedforward neural networks and particle swarm optimization
Huang, Rui
He, Mingyi
[J]. 2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS, 2007, : 692 - 696
[4] Integrated feature and parameter optimization for an evolving spiking neural network: Exploring heterogeneous probabilistic models
Schliebs, Stefan
Defoin-Platel, Michael
Worner, Sue
Kasabov, Nikola
[J]. NEURAL NETWORKS, 2009, 22 (5-6) : 623 - 632
[5] Particle Swarm Optimization for Hyper-Parameter Selection in Deep Neural Networks
Lorenzo, Pablo Ribalta
Nalepa, Jakub
Kawulok, Michal
Sanchez Ramos, Luciano
Ranilla Pastor, Jose
[J]. PROCEEDINGS OF THE 2017 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'17), 2017, : 481 - 488
[6] Hyper-Parameter Selection in Deep Neural Networks Using Parallel Particle Swarm Optimization
Lorenzo, Pablo Ribalta
Nalepa, Jakub
Sanchez Ramos, Luciano
Ranilla Pastor, Jose
[J]. PROCEEDINGS OF THE 2017 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION (GECCO'17 COMPANION), 2017, : 1864 - 1871
[7] The Enhancement of Evolving Spiking Neural Network with Dynamic Population Particle Swarm Optimization
Said, Nur Nadiah Md.
Hamed, Haza Nuzly Abdull
Abdullah, Afnizanfaizal
[J]. MODELING, DESIGN AND SIMULATION OF SYSTEMS, ASIASIM 2017, PT II, 2017, 752 : 95 - 103
[8] Evolving Product Unit Neural Networks with Particle Swarm Optimization
Huang, Rong
Tong, Shurong
[J]. PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON IMAGE AND GRAPHICS (ICIG 2009), 2009, : 624 - 628
[9] Analyzing the Dynamics of the Simultaneous Feature and Parameter Optimization of an Evolving Spiking Neural Network
Schliebs, Stefan
Defoin-Platel, Michael
Kasabov, Nikola
[J]. 2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010, 2010,
[10] FEATURE SELECTION AND PARAMETER OPTIMIZATION FOR SUPPORT VECTOR MACHINES USING PARTICLE SWARM OPTIMIZATION AND HARMONY SEARCH
Han, Jihee
Seo, Yoonho
[J]. INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE, 2021, 28 (01): : 1 - 13

← 1 2 3 4 5 →