Frankenstein PSO Applied to Neural Network Weights and Architectures

被引：0

作者：

de Lima, Natalia Flora ^{[1
]}

Ludermir, Teresa Bernarda ^{[1
]}

机构：

[1] Univ Fed Pernambuco, UFPE, Ctr Informat, Recife, PE, Brazil

来源：

2011 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2011年

关键词：

Particle Swarm Optimization; Neural Networks; Classification Problems; PARTICLE SWARM;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper we present the FPSOA-FPSOP, a modified version of Frankstein Particle Swarm Optimization (FPSO), which is used to adjust the weights and architectures of a feed-forward neural network. To evaluate the algorithm we used benchmark classification problems in medical care area. The results were compared with other algorithms which use the same methodology to find out the weights and architectures.

引用

页码：2452 / 2456

页数：5

共 50 条

[31] Comparative Analysis of a Neural Network with Calculated Weights and a Neural Network with Random Generation of Weights Based on the Training Dataset Size
Geidarov, P. Sh
[J]. OPTICAL MEMORY AND NEURAL NETWORKS, 2022, 31 (03) : 309 - 321
[32] Comparative Analysis of a Neural Network with Calculated Weights and a Neural Network with Random Generation of Weights Based on the Training Dataset Size
P. Sh. Geidarov
[J]. Optical Memory and Neural Networks, 2022, 31 : 309 - 321
[33] Regularization-based pruning of irrelevant weights in deep neural architectures
Giovanni Bonetta
Matteo Ribero
Rossella Cancelliere
[J]. Applied Intelligence, 2023, 53 : 17429 - 17443
[34] Regularization-based pruning of irrelevant weights in deep neural architectures
Bonetta, Giovanni
Ribero, Matteo
Cancelliere, Rossella
[J]. APPLIED INTELLIGENCE, 2023, 53 (14) : 17429 - 17443
[35] Neural network training using stochastic PSO
Chen, Xin
Li, Yangmin
[J]. NEURAL INFORMATION PROCESSING, PT 2, PROCEEDINGS, 2006, 4233 : 1051 - 1060
[36] Face Detection Based on PSO and Neural Network
Wang, Yanjiang
Liu, Xiaoping
Suo, Peng
[J]. ICSP: 2008 9TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, VOLS 1-5, PROCEEDINGS, 2008, : 1521 - 1524
[37] Architectures of neural networks applied for LVCSR language modeling
Gajecki, Leszek
[J]. NEUROCOMPUTING, 2014, 133 : 46 - 53
[38] Prior probability weights and neural network learning
Matsuyama, Y
Furukawa, S
Ikeda, T
[J]. PROGRESS IN CONNECTIONIST-BASED INFORMATION SYSTEMS, VOLS 1 AND 2, 1998, : 267 - 270
[39] A feedback neural network with weights of sinusoidal functions
Li Cheng
Shi Dan
Zou Yun-Ping
[J]. ACTA PHYSICA SINICA, 2012, 61 (07)
[40] Context-sensitive weights for a neural network
Arritt, RP
Turner, RM
[J]. MODELING AND USING CONTEXT, PROCEEDINGS, 2003, 2680 : 29 - 39

← 1 2 3 4 5 →