Imperialist competitive algorithm optimized artificial neural networks for UCAV global path planning

Neurocomputing

Volumn 125, Issue , 2014, Pages 166-171

  Duan, Haibin ^a   Huang, Linzhi ^a  

^a BEIHANG UNIVERSITY   (China)

Author keywords

Artificial neural network (ANN); Global path planning; Imperialist competitive algorithm (ICA); Unmanned combat aerial vehicle (UCAV)

Indexed keywords

ARTIFICIAL BEE COLONY ALGORITHMS (ABC); GLOBAL PATH PLANNING; IMPERIALIST COMPETITIVE ALGORITHM (ICA); IMPERIALIST COMPETITIVE ALGORITHMS; OPTIMAL PATH PLANNING; PROBABILITY MODELING; REPETITIVE TASK; UNMANNED COMBAT AERIAL VEHICLES;

EVOLUTIONARY ALGORITHMS; MILITARY VEHICLES; NEURAL NETWORKS; OPTIMIZATION;

MOTION PLANNING;

AIRCRAFT; ALGORITHM; ARTICLE; ARTIFICIAL BEE COLONY ALGORITHM; ARTIFICIAL NEURAL NETWORK; GLOBAL POSITIONING SYSTEM; IMPERIALIST COMPETITIVE ALGORITHM; LEARNING ALGORITHM; MACHINE LEARNING; ORGANIZATION AND MANAGEMENT; PRIORITY JOURNAL; UNMANNED COMBAT AERIAL VEHICLE; VELOCITY;

EID: 84888025640     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.09.039     Document Type: Article

References (14)

1. Zheng C.W., Li L., Xu F.J. Evolutionary route planner for unmanned air vehicles. IEEE Trans. Rob. Autom. 2005, 21(4):609-620.
2. Duan H.B., Shao S., Su B.W., Zhang L. New development thoughts on the bio-inspired intelligence based control for unmanned combat aerial vehicle. Sci. China Technol. Sci. 2010, 53(8):2025-2031.
3. Duan H.B., Liu S.Q. Unmanned air/ground vehicles heterogeneous cooperative techniques: current status and prospects. Sci. China Technol. Sci. 2010, 53(5):1349-1355.
4. Pehlivanoglu Y.V. A new vibrational genetic algorithm enhanced with a Voronoi diagram for path planning of autonomous UAV. Aerosp. Sci. Technol. 2012, 16(1):47-55.
5. Ye W., Ma D.W., Fan H.D. Algorithm for low altitude penetration aircraft path planning with improved ant colony algorithm. Chin. J. Aeronaut. 2005, 18(4):304-309.
6. A.G. Esmaeil, C. Lucas, Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition, in: Proceedings of 2007 IEEE Congress on Evolutionary Computation, Singapore, 2007, pp. 4661-4667.
7. Duan H.B., Xu C.F., Liu S.Q., Shao S. Template matching using chaotic imperialist competitive algorithm. Pattern Recognition Lett. 2010, 31(13):1868-1875.
8. Xu C.F., Duan H.B., Liu F. Chaotic artificial bee colony approach to Uninhabited Combat Air Vehicle (UCAV) path planning. Aerosp. Sci. Technol. 2010, 14(8):535-541.
9. Duan H.B., Yu Y.X., Zhang X.Y., Shao S. Three-dimension path planning for UCAV using hybrid meta-heuristic ACO-DE algorithm. Simulation Model. Pract. Theory 2010, 18(8):1104-1115.
10. Y.J. Zhu, J. Chang, S.G. Wang, A new path-planning algorithm for mobile robot based on neural network, in: Proceedings of IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering, vol. 3, 2002, pp. 1570-1573.
11. Wei G.W., Fu M.Y. An algorithm based on neural network for mobile robot path planning. Comput. Simulation 2010, 27(7):112-116.
12. Liang J., Song K.P. The application of neural network in mobile robot path planning. J. Syst. Simulation 2010, 22(1):269-272.
13. Esmaeil A.G., Hashemzadeh F., Rajabioun R. Colonial competition algorithm: a novel approach for PID controller design in MIMO distillation column process. Int. J. Intelligent Comput. Cybern. 2008, 1(3):337-355.
14. Zhang X.Y., Duan H.B., Yu Y.X. Receding horizon control for multi-UAVs close formation control based on differential evolution. Sci. China Inf. Sci. 2010, 53(2):223-235.