Results 31 to 40 of about 20,311 (188)
On Optimizing Deep Convolutional Neural Networks by Evolutionary Computing
CoRR, 2018 Optimization for deep networks is currently a very active area of research. As neural networks become deeper, the ability in manually optimizing the network becomes harder. Mini-batch normalization, identification of effective respective fields, momentum updates, introduction of residual blocks, learning rate adoption, etc.
M. U. Bigumjith Dias +2 more
openaire +2 more sources
Evolutionary neural cascade search across supernetworks [PDF]
, 2022 To achieve excellent performance with modern neural networks, having the right network architecture is important. Neural Architecture Search (NAS) concerns the automatic discovery of task-specific network architectures.
Chebykin, Alexander (author) +8 more
core +1 more source
A Review Of Methods For Encoding Neural Network Topologies In Evolutionary Computation
ECMS 2011 Proceedings edited by: T. Burczynski, J. Kolodziej, A. Byrski, M. Carvalho, 2011 This paper describes various methods used to encode artificial neural networks to chromosomes to be used in evolutionary computation. The target of this review is to cover the main techniques of network encoding and make it easier to choose one when implementing a custom evolutionary algorithm for finding the network topology.
Jozef Fekiac +2 more
openaire +3 more sources
Fuzzy evolutionary algorithms and neural networks in uncertain optimization problems
Computer Assisted Methods in Engineering and Science, 2022 This paper is devoted to the application of the evolutionary algorithms and artificial neural networks to uncertain optimization problems in which some parameters are described by fuzzy numbers.
Piotr Orantek
doaj
Continuous Evolutionary Neural Architecture Search Based on Biased Sampling [PDF]
Jisuanji gongchengNeural Architecture Search(NAS) typically requires a considerable amount of time and computing resources due to the independent performance evaluation of each architecture it searches.
YU XUE, Changchang LU
doaj +1 more source
Soft Computing Techniques for Dependable Cyber-Physical Systems
IEEE Access, 2019 Cyber-physical systems (CPSs) were envisaged as a way to manipulate the objects in the physical world through computer intelligence. This is usually done by providing a communication bridge between actuation and computing elements.
Muhammad Atif +7 more
doaj +1 more source
PRE-NAS: Predictor-assisted Evolutionary Neural Architecture Search [PDF]
, 2022 Neural architecture search (NAS) aims to automate architecture engineering in neural networks. This often requires a high computational overhead to evaluate a number of candidate networks from the set of all possible networks in the search space during ...
Fayek, HM +9 more
core +1 more source
An evolutionary computing frame work toward object extraction from satellite images
Egyptian Journal of Remote Sensing and Space Sciences, 2013 Image interpretation domains have witnessed the application of many intelligent methodologies over the past decade; however the effective use of evolutionary computing techniques for feature detection has been less explored.
P.V. Arun, S.K. Katiyar
doaj +1 more source
A Surrogate-Assisted Adaptive Bat Algorithm for Large-Scale Economic Dispatch
Energies, 2023 Large-scale grids have gradually become the dominant trend in power systems, which has increased the importance of solving the challenges associated with large-scale economic dispatch (LED).
Aokang Pang +3 more
doaj +1 more source
IEEE Access, 2023 The echo state network (ESN) is a cutting-edge reservoir computing technique designed to handle time-dependent data, making it highly effective for addressing time series prediction tasks.
Zohaib Ahmad +4 more
doaj +1 more source