Research on ship traffic organization optimization based on improved grey wolf algorithm

2021 ◽  
Author(s):  
Biao Jin ◽  
Zhongyi Zheng
Keyword(s):  
Grey Wolf ◽  
Ship Traffic ◽  
Traffic Organization ◽  
Grey Wolf Algorithm

scholarly journals A hybridized model based on neural network and swarm intelligence-grey wolf algorithm for spatial prediction of urban flood-inundation

2021 ◽  
pp. 126854
Author(s):  
Hamid Darabi ◽  
Ali Torabi Haghighi ◽  
Omid Rahmati ◽  
Abolfazl Jalali Shahrood ◽  
Sajad Rouzbeh ◽  
...  
Keyword(s):  
Neural Network ◽  
Swarm Intelligence ◽  
Spatial Prediction ◽  
Flood Inundation ◽  
Grey Wolf ◽  
Urban Flood ◽  
Model Based ◽  
Grey Wolf Algorithm

scholarly journals A Novel Coverage Optimization Strategy Based on Grey Wolf Algorithm Optimized by Simulated Annealing for Wireless Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yong Zhang ◽  
Li Cao ◽  
Yinggao Yue ◽  
Yong Cai ◽  
Bo Hang
Keyword(s):  
Wireless Sensor Networks ◽  
Simulated Annealing ◽  
Sensor Networks ◽  
Optimization Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Coverage Optimization ◽  
Grey Wolf Algorithm

The coverage optimization problem of wireless sensor network has become one of the hot topics in the current field. Through the research on the problem of coverage optimization, the coverage of the network can be improved, the distribution redundancy of the sensor nodes can be reduced, the energy consumption can be reduced, and the network life cycle can be prolonged, thereby ensuring the stability of the entire network. In this paper, a novel grey wolf algorithm optimized by simulated annealing is proposed according to the problem that the sensor nodes have high aggregation degree and low coverage rate when they are deployed randomly. Firstly, the mathematical model of the coverage optimization of wireless sensor networks is established. Secondly, in the process of grey wolf optimization algorithm, the simulated annealing algorithm is embedded into the grey wolf after the siege behavior ends and before the grey wolf is updated to enhance the global optimization ability of the grey wolf algorithm and at the same time improve the convergence rate of the grey wolf algorithm. Simulation experiments show that the improved grey wolf algorithm optimized by simulated annealing is applied to the coverage optimization of wireless sensor networks. It has better effect than particle swarm optimization algorithm and standard grey wolf optimization algorithm, has faster optimization speed, improves the coverage of the network, reduces the energy consumption of the nodes, and prolongs the network life cycle.

scholarly journals Modified grey wolf method for optimization of PM motors

2019 ◽  
Vol 28 ◽  
pp. 01020
Author(s):  
Łukasz Knypiński
Keyword(s):  
Mathematical Model ◽  
Permanent Magnet ◽  
Permanent Magnet Synchronous Motor ◽  
Computer Software ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Grey Wolf ◽  
Electromagnetic Devices ◽  
The Mathematical Model ◽  
Grey Wolf Algorithm

The paper presents an algorithm and computer software for the optimization of electromagnetic devices. The mathematical model of the optimization method was presented. The modification of the classical grey wolf algorithm was developed. The modification consists in decreasing the coefficient responsible for the possibility of migration individuals in the permissible area of solved task. The optimization procedure was elaborated in the Borland Delphi environment. The optimization of the rotor of the line-start permanent magnet synchronous motor has been carried out. It has been pointed out that the grey wolf algorithm is effective method for optimization of electromagnetic devices.

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