Figure - available via license: Creative Commons Attribution-NonCommercial 4.0 International
Content may be subject to copyright.
Training time of each algorithm (unit: s)
Contexts in source publication
Context 1
... is evenly distributed on the random number 1 , 0 .Compared with the genetic algorithm and particle swarm algorithm, the firefly algorithm has no mutation and cross operation, so it is easier to implement and operate, and the convergence speed is faster. The optimal algorithm of FA, GA, and PSO is shown in Table 1, where the population size is 100, the number of iterations is 50, the light absorption coefficient of FA algorithm is 1, and the maximum attractive force is 1. PSO algorithm learning factor 2 ...Context 2
... the crossover probability and mutation probability of GA are both 0.5. Table 1 that when the convergence to a given precision, compared to the genetic algorithm and particle swarm algorithm, the running time of firefly algorithm is shorter, so the firefly algorithm is selected to optimize the extreme learning machine algorithm. ...Similar publications
Fault diagnosis of rolling bearings has become a critical measure to ensure the security, efficiency, and availability of wind turbine systems. In this work, an approach called a transfer deep learning network is reported to resolve the drawbacks of existing rolling bearing fault algorithms on the basis of deep learning, such as large training para...
To address the problems that the noise in the bearing vibration data affects the fault diagnosis capability of the model, the intelligent diagnosis model requires a large amount of historical data, and the severity of bearing faults is unknown. A cross-condition quantitative diagnosis method for bearing faults based on Improved Deep Residual Shrink...
A lightweight neural network fault diagnosis method based on Gramian angular field (GAF) feature map construction and efficient channel attention (ECA) optimization is presented herein to address the problem of the complex structure of traditional neural networks in bearing fault diagnosis. Firstly, a GAF is used to encode vibration signals into a...
