Changtao Wang¹, Honghua Dai^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.010943

Abstract Orbital uncertainty propagation is fundamental in space situational awareness-related missions such as orbit prediction and tracking. Linear models and full nonlinear Monte Carlo simulations were primarily used to propagate uncertainties [1]. However, these methods hampered the application due to low precision and intensive computation. Over the past two decades, numerous nonlinear uncertainty propagators have been proposed. Among these methods, the state transition tensor (STT) method has been widely used due to its controllable accuracy and high efficiency [2]. However, this method has two drawbacks. First, its semi-analytical formulation is too intricate to implement, which hinders… More >

Liang Zeng^1,2, Mai Hu¹, Chenning Zhang¹, Quan Yuan¹, Shanshan Wang^1,2,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1677-1709, 2024, DOI:10.32604/cmc.2024.049717 - 18 July 2024

Abstract Optimization algorithms play a pivotal role in enhancing the performance and efficiency of systems across various scientific and engineering disciplines. To enhance the performance and alleviate the limitations of the Northern Goshawk Optimization (NGO) algorithm, particularly its tendency towards premature convergence and entrapment in local optima during function optimization processes, this study introduces an advanced Improved Northern Goshawk Optimization (INGO) algorithm. This algorithm incorporates a multifaceted enhancement strategy to boost operational efficiency. Initially, a tent chaotic map is employed in the initialization phase to generate a diverse initial population, providing high-quality feasible solutions. Subsequently, after… More >

M. Rajalakshmi¹, V. Saravanan², V. Arunprasad³, C. A. T. Romero⁴, O. I. Khalaf⁵, C. Karthik^1,*

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 339-359, 2022, DOI:10.32604/iasc.2022.021696 - 26 October 2021

Abstract In sugar production, model parameter estimation and controller tuning of the nonlinear clarification process are major concerns. Because the sugar industry’s clarification process is difficult and nonlinear, obtaining the exact model using identification methods is critical. For regulating the clarification process and identifying the model parameters, this work presents a state transition algorithm (STA). First, the model parameters for the clarifier are estimated using the normal system identification process. The STA is then utilized to improve the accuracy of the system parameters that have been identified. Metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm More >

Hui Wang¹, Chuanhan Zhu¹, Zihao Shen^1,*, Dengwei Lin², Kun Liu¹, MengYao Zhao³

Computer Systems Science and Engineering, Vol.38, No.1, pp. 103-117, 2021, DOI:10.32604/csse.2021.014680 - 01 April 2021

Abstract Computer networks face a variety of cyberattacks. Most network attacks are contagious and destructive, and these types of attacks can be harmful to society and computer network security. Security evaluation is an effective method to solve network security problems. For accurate assessment of the vulnerabilities of computer networks, this paper proposes a network security risk assessment method based on a Bayesian network attack graph (B_NAG) model. First, a new resource attack graph (RAG) and the algorithm E-Loop, which is applied to eliminate loops in the B_NAG, are proposed. Second, to distinguish the confusing relationships between… More >