Halah Hasan Mahmoud¹, Marwan Kadhim Mohammed Al-Shammari¹, Gehad Abdullah Amran^2,3,*, Elsayed Tag eldin^4,*, Ala R. Alareqi⁵, Nivin A. Ghamry⁶, Ehaa ALnajjar⁷, Esmail Almosharea⁸

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 573-589, 2023, DOI:10.32604/cmc.2023.039363 - 08 June 2023

Abstract Utilizing artificial intelligence (AI) to protect smart coastal cities has become a novel vision for scientific and industrial institutions. One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles (UVs) for anti-submarine attacks. This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy. The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach, and the Re-fragmentation strategy is used in the Network… More >

Zhigang Deng^1,*, Zhenzhong Chu², Zaman Mohammed Tousif³

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1503-1515, 2020, DOI:10.32604/iasc.2020.010798 - 24 December 2020

Abstract Trajectory tracking control can be considered as one of the main researches of unmanned underwater vehicles (UUV). The bio-inspired neurodynamics model was used to make the output continuous and smooth for the inflection points to deal with the speed jump of the conventional tracking controller for discrete trajectories. A horizon-plane trajectory tracking control law is designed using the bio-inspired neurodynamics model and sliding-mode method without chattering. Finally, the simulation of the mentioned two methods is compared with the results showing this as effective and feasible. More >