Swarm intelligence based approach for efficient training of regressive neural networks-Reference-Cited by-同舟云学术

Swarm intelligence based approach for efficient training of regressive neural networks

Published:2019-11-23 Issue:14 Volume:32 Page:10693-10704
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Lozito Gabriele Maria^ORCID,Salvini Alessandro

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/s00521-019-04606-x.pdf

Reference43 articles.

1. Cybenko G (1989) Approximation by superpositions of a sigmoidal function. Math Control Signals Syst (MCSS) 2(4):303–314

2. Hornik K, Stinchcombe M, White H (1989) Multilayer feedforward networks are universal approximators. Neural Netw 2(5):359–366

3. Whalen P, Brio M, Moloney JV (2015) Exponential time-differencing with embedded Runge–Kutta adaptive step control. J Comput Phys 280:579–601

4. Butcher JC (2016) Numerical methods for ordinary differential equations. Wiley, New York

5. Khan K, Sahai A (2012) A comparison of BA, GA, PSO, BP and LM for training feed forward neural networks in e-learning context. Int J Intell Syst Appl 4(7):23

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Autoencoders for Hourly Load Profile Reconstruction in Renewable Energy Communities;IEEE EUROCON 2023 - 20th International Conference on Smart Technologies;2023-07-06

2. Direct and Inverse Neural Modelling of Buildings HVAC Systems;IEEE EUROCON 2023 - 20th International Conference on Smart Technologies;2023-07-06

3. A Survey on the Optimization of Artificial Neural Networks Using Swarm Intelligence Algorithms;IEEE Access;2023

4. Engineering Financial Performance Evaluation of Wireless Network Based on Intelligent Neural Network Model;Wireless Communications and Mobile Computing;2021-12-10

5. Time-Domain Circuit Modelling for Hybrid Supercapacitors;Energies;2021-10-19