Jian Wang¹, Hui Qi¹, Feilong Jiang^2,*, Biao Jiang³, Tiankui Sun⁴, Lingyi Ji¹, Yajun Zhao², Feifei Bu²

Energy Engineering, Vol.122, No.12, pp. 4873-4897, 2025, DOI:10.32604/ee.2025.069071 - 27 November 2025

Abstract To enhance power supply reliability and reduce customer outage time, Mobile Emergency Power Supply Vehicles (MEPSVs), including Mobile Diesel Generator Vehicles (MDGVs) and Mobile Energy Storage Vehicles (MESVs), have become indispensable sources for grid maintenance and disaster response. However, in practice, relying solely on MESVs is constrained by battery capacity, making it difficult to meet long-duration power demands. Conversely, using only MDGVs often results in low efficiency and high fuel consumption under fluctuating load conditions, posing challenges to achieving economical and efficient power supply. To address these issues, this paper investigates the parallel power supply… More >

Hajer Hafaiedh^1,2, Adel Mahjoub³, Yahia Saoudi⁴, Anouar Benamor², Okba Taouali^5,*, Kamel Zidi⁶, Wad Ghaban⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 571-596, 2025, DOI:10.32604/cmes.2025.071642 - 30 October 2025

Abstract Several optimization methods, such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), are used to select the most suitable Static Synchronous Compensator (STATCOM) technology for the optimal operation of the power system, as well as to determine its optimal location and size to minimize power losses. An IEEE 14 bus system, integrating three wind turbines based on Squirrel Cage Induction Generators (SCIGs), is used to test the applicability of the proposed algorithms. The results demonstrate that these algorithms are capable of selecting the most appropriate technology while optimally sizing and locating the STATCOM to More >

Farzad Mohebbi^*

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1417-1441, 2025, DOI:10.32604/fhmt.2025.069024 - 31 October 2025

Abstract An inverse analysis is presented to estimate line heat source in two-dimensional steady-state and transient heat transfer problems. A constant heat source is considered in the steady-state heat transfer problem (a parameter estimation problem) and a time-varying heat source is considered in the transient heat transfer problem (a function estimation problem). Since a general irregular 2D heat conducting body is considered, a body-fitted grid generation is used to mesh the domain. Then governing equations and associated boundary and initial conditions are transformed from the physical domain to the computational domain and finite difference method is… More >

Hari Mohan Rai^1,#, Chandra Mukherjee^2,#, Joon Yoo¹, Hanaa A. Abdallah³, Saurabh Agarwal^4,*, Wooguil Pak^4,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5723-5745, 2025, DOI:10.32604/cmc.2025.070391 - 23 October 2025

Abstract A hybrid Compressed Sensing and Primal-Dual Wavelet (CSP-PDW) technique is proposed for the compression and reconstruction of ECG signals. The compression and reconstruction algorithms are implemented using four key concepts: Sparsifying Basis, Restricted Isometry Principle, Gaussian Random Matrix, and Convex Minimization. In addition to the conventional compression sensing reconstruction approach, wavelet-based processing is employed to enhance reconstruction efficiency. A mathematical model of the proposed algorithm is derived analytically to obtain the essential parameters of compression sensing, including the sparsifying basis, measurement matrix size, and number of iterations required for reconstructing the original signal and determining More >

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 >