scholarly journals A Novel Method for Image Segmentation Based on Simplified Pulse Coupled Neural Network and Gbest Led Gravitational Search Algorithm

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 21310-21330 ◽  
Author(s):  
Keming Jiao ◽  
Zhongliang Pan
Keyword(s):  
Neural Network ◽  
Image Segmentation ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Pulse Coupled Neural Network ◽  
Novel Method ◽  
Gravitational Search

Neural network and fuzzy system for the tuning of Gravitational Search Algorithm parameters

2018 ◽  
Vol 102 ◽  
pp. 234-244 ◽  
Author(s):  
Danilo Pelusi ◽  
Raffaele Mascella ◽  
Luca Tallini ◽  
Janmenjoy Nayak ◽  
Bighnaraj Naik ◽  
...  
Keyword(s):  
Neural Network ◽  
Fuzzy System ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Gravitational Search

scholarly journals Inverse calculation of demolition robot based on gravitational search algorithm and differential evolution neural network

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092529
Author(s):  
Jianzhong Huang ◽  
Yuwan Cen ◽  
Nenggang Xie ◽  
Xiaohua Ye
Keyword(s):  
Neural Network ◽  
Convergence Rate ◽  
Differential Evolution ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Population Diversity ◽  
Measuring Point ◽  
Mapping Model ◽  
Gravitational Search ◽  
Set Up

For the inverse calculation of laser-guided demolition robot, its global nonlinear mapping model from laser measuring point to joint cylinder stroke has been set up with an artificial neural network. Due to the contradiction between population diversity and convergence rate in the optimization of complex neural networks by using differential evolution, a gravitational search algorithm and differential evolution is proposed to accelerate the convergence rate of differential evolution population driven by gravity. Gravitational search algorithm and differential evolution is applied to optimize the inverse calculation neural network mapping model of demolition robot, and the algorithm simulation shows that gravity can effectively regulate the convergence process of differential evolution population. Compared with the standard differential evolution, the convergence speed and accuracy of gravitational search algorithm and differential evolution are significantly improved, which has better optimization stability. The calculation results show that the output accuracy of this gravitational and differential evolution neural network can meet the calculation requirements of the positioning control of demolition robot’s manipulator. The optimization using gravitational search algorithm and differential evolution is done with the connection weights of a neural network in this article, and as similar techniques can be applied to the other hyperparameter optimization problem. Moreover, such an inverse calculation method can provide a reference for the autonomous positioning of large hydraulic series manipulator, so as to improve the robotization level of construction machinery.

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