Fawei Ge
Bohai University
10 Papers
29 Citations
Fawei Ge is an academic researcher from Bohai University. The author has contributed to research in topics: Computer science & Motion planning. The author has an hindex of 6, co-authored 9 publications.
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Papers
Path planning of multiple UAVs with online changing tasks by an ORPFOA algorithm
TL;DR: An improved fruit fly optimization algorithm (named ORPFOA) is proposed to solve the path planning problem in both initial task sequences and new task sequences after tasks change, in which the optimal reference point and a distance cost matrix are used to reach both faster solving and higher optimizing precision for the optimal flight path.
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Path planning of UAV for oilfield inspections in a three-dimensional dynamic environment with moving obstacles based on an improved pigeon-inspired optimization algorithm
TL;DR: Simulation results show that the proposed PIOFOA method is more effective than some other methods, and a pigeon-inspired optimization algorithm is proposed to solve problems about path planning in a three-dimensional dynamic environment of oilfields.
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Path Planning of UAV for Oilfield Inspection Based on Improved Grey Wolf Optimization Algorithm
Fawei Ge,Kun Li,Wensu Xu,Yi’an Wang +3 more
- 03 Jun 2019
TL;DR: An improved grey wolf optimization algorithm is proposed for the path planning of UAV in oilfield environment and compared with some other methods, the simulation results show that the improvedgrey wolf optimize algorithm is effective.
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Tracking a dynamic invading target by UAV in oilfield inspection via an improved bat algorithm
TL;DR: An improved bat algorithm is proposed to improve the local searching ability of the bat algorithm (BA) which uses a food searching mechanism in the fruit fly optimization algorithm (FOA), which can effectively keep the tracking distance between the UAV and the target being about 55m, which is better than some other methods.
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Online fault diagnosis for sucker rod pumping well by optimized density peak clustering.
TL;DR: In this article, five feature vectors are extracted using Freeman chain codes and an optimized density peak clustering (DPC) method is proposed to realize online diagnosis solved by an improved brain storm optimization (BSO) algorithm, in which the cloud model is adopted to generate new solutions in the searching space.
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