Kuo Li^1,*, Aimin Wang¹, Limin Wang¹, Yuetan Zhao¹, Xinyu Zhu²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 617-637, 2025, DOI:10.32604/cmes.2025.061242 - 11 April 2025

Abstract A Bayesian network reconstruction method based on norm minimization is proposed to address the sparsity and iterative divergence issues in network reconstruction caused by noise and missing values. This method achieves precise adjustment of the network structure by constructing a preliminary random network model and introducing small-world network characteristics and combines L1 norm minimization regularization techniques to control model complexity and optimize the inference process of variable dependencies. In the experiment of game network reconstruction, when the success rate of the L1 norm minimization model’s existence connection reconstruction reaches 100%, the minimum data required is… More >

Yihao Chen¹, Yongxing Shen^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011251

Abstract The phase field method for fracture has become mainstream for fracture simulation. It transforms the crack nucleation problem into a minimization problem of the sum of the elastic potential energy and the crack surface energy. Because of the biconvexity of its energy functional, there is an energy barrier between local minima with and without a crack, resulting it difficult for standard methods, such as the Newton method, to converge to a cracked solution when starting from a solid without crack, especially when the material and the geometry are uniform, even if current cracked solution with… More >

Yu Zhou¹, Yun Zhang¹, Guowei Li¹, Hang Yang¹, Wei Zhang¹, Ting Lyu², Yueqiang Xu^2,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1809-1829, 2024, DOI:10.32604/cmc.2024.050975 - 15 August 2024

Abstract In current research on task offloading and resource scheduling in vehicular networks, vehicles are commonly assumed to maintain constant speed or relatively stationary states, and the impact of speed variations on task offloading is often overlooked. It is frequently assumed that vehicles can be accurately modeled during actual motion processes. However, in vehicular dynamic environments, both the tasks generated by the vehicles and the vehicles’ surroundings are constantly changing, making it difficult to achieve real-time modeling for actual dynamic vehicular network scenarios. Taking into account the actual dynamic vehicular scenarios, this paper considers the real-time… More >

Mohammad Mehdi Sharifi Nevisi¹, Elnaz Bashir², Diego Martín^3,*, Seyedkian Rezvanjou⁴, Farzaneh Shoushtari⁵, Ehsan Ghafourian²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3971-3991, 2024, DOI:10.32604/cmc.2024.047875 - 26 March 2024

Abstract This paper focuses on wireless-powered communication systems, which are increasingly relevant in the Internet of Things (IoT) due to their ability to extend the operational lifetime of devices with limited energy. The main contribution of the paper is a novel approach to minimize the secrecy outage probability (SOP) in these systems. Minimizing SOP is crucial for maintaining the confidentiality and integrity of data, especially in situations where the transmission of sensitive data is critical. Our proposed method harnesses the power of an improved biogeography-based optimization (IBBO) to effectively train a recurrent neural network (RNN). The… More >

Yixuan Yu, Yulin Wang^*, Qingcheng Li, Bowen Jiao

Energy Engineering, Vol.121, No.3, pp. 769-788, 2024, DOI:10.32604/ee.2023.044042 - 27 February 2024

Abstract The plug-in hybrid vehicles (PHEV) technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks. Meanwhile, plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies (EMS). Therefore, a series hybrid system is constructed based on a 100-ton mining dump truck in this paper. And inspired by the dynamic programming (DP) algorithm, a predictive equivalent consumption minimization strategy (P-ECMS) based on the DP optimization result is proposed. Based on the optimal control manifold and the SOC reference trajectory obtained by the More >

Paramjeet Kaur¹, Krishna Teerth Chaturvedi¹, Mohan Lal Kolhe^2,*

Energy Engineering, Vol.121, No.3, pp. 557-579, 2024, DOI:10.32604/ee.2024.043159 - 27 February 2024

Abstract In the increasingly decentralized energy environment, economical power dispatching from distributed generations (DGs) is crucial to minimizing operating costs, optimizing resource utilization, and guaranteeing a consistent and sustainable supply of electricity. A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability. The choice of optimization technique for economic power dispatching from DGs depends on a number of factors, such as the size and complexity of the power system, the availability of computational resources, and… More >

Wen Sun¹, Meijing Li², Guoxiang Li¹, Ke Sun^1,*, Shuzhan Bai^1,*

Energy Engineering, Vol.121, No.1, pp. 95-110, 2024, DOI:10.32604/ee.2023.042096 - 27 December 2023

Abstract Proton exchange membrane fuel cells are widely regarded as having the potential to replace internal combustion engines in vehicles. Since fuel cells cannot recover energy and have a slow dynamic response, they need to be used with different power sources. Developing efficient energy management strategies to achieve excellent fuel economy is the goal of research. This paper proposes an adaptive equivalent fuel minimum consumption strategy (AECMS) to solve the problem of the poor economy of the whole vehicle caused by the wrong selection of equivalent factors (EF) in traditional ECMS. In this method, the kinematics More >

C. Rajathi, P. Rukmani^*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 733-756, 2023, DOI:10.32604/cmc.2023.041507 - 31 October 2023

Abstract Considering the recent developments in the digital environment, ensuring a higher level of security for networking systems is imperative. Many security approaches are being constantly developed to protect against evolving threats. An ensemble model for the intrusion classification system yielded promising results based on the knowledge of many prior studies. This research work aimed to create a more diverse and effective ensemble model. To this end, selected six classification models, Logistic Regression (LR), Naive Bayes (NB), K-Nearest Neighbor (KNN), Decision Tree (DT), Support Vector Machine (SVM), and Random Forest (RF) from existing study to run… More >

Jinyu Gu¹, Jinping Qu¹, Yingjun Wang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09161

Abstract In the topology optimization problem of mechanical structures, the optimization objectives are mainly focused on the compliance minimization, displacement minimization, stress minimization, and so on. However, in practical engineering, these kinds of optimization objectives do not meet all the requirements. Some structures, such as wind turbine blades and engine blades of aircrafts, are required to maintain a superior aerodynamic shape under external loads. This puts a higher requirement on the local deformation homogenization of the structure. Therefore, we proposed a topology optimization method for the minimization of local relative displacement differences considering stress constraints. First,… More >

Fadwa Alrowais¹, Jaber S. Alzahrani², Radwa Marzouk¹, Abdullah Mohamed³, Gouse Pasha Mohammed^4,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6145-6160, 2023, DOI:10.32604/cmc.2023.038300 - 29 April 2023

Abstract Combined Economic and Emission Dispatch (CEED) task forms multi-objective optimization problems to be resolved to minimize emission and fuel costs. The disadvantage of the conventional method is its incapability to avoid falling in local optimal, particularly when handling nonlinear and complex systems. Metaheuristics have recently received considerable attention due to their enhanced capacity to prevent local optimal solutions in addressing all the optimization problems as a black box. Therefore, this paper focuses on the design of an improved sand cat optimization algorithm based CEED (ISCOA-CEED) technique. The ISCOA-CEED technique majorly concentrates on reducing fuel costs More >