Jingfu Yan, Huachun Zhou^*, Xiaojing Fan, Aoran Huang

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084537 - 28 August 2026

Abstract Artificial Intelligence (AI) has been widely used to detect complex attacks and abnormal behaviors in intelligent communication networks. However, existing studies are often limited to a single scenario or technical route, making it difficult to systematically explain the roles, boundaries, and collaboration mechanisms of different AI-integrated detection technologies. To address this gap, this paper reviews AI-integrated detection technologies in intelligent communication networks from both scenario and technical perspectives. From the perspective of application scenarios, the paper summarizes the requirements and characteristics of AI detection in cloud networks, edge computing, satellite and space networks, and Internet… More >

Anyu Hong¹, Zheng-Yang Li^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084527 - 28 August 2026

Abstract The simulation of non-Fourier heat conduction poses significant computational challenges, particularly in periodic structures such as thermal wave crystals or thermal metamaterials. This paper employs the Local Radial Basis Function Collocation Method (LRBFCM) to evaluate the wave-like propagation characteristics inherent to the non-Fourier heat transfer process. Utilizing LRBFCM, the complex band structure of thermal wave crystals is calculated, and these findings are validated against temperature responses in the frequency domain. Finally, this study introduces a robust methodology for predicting non-Fourier heat conduction behavior in thermal metamaterials. In a word, this paper investigates the application of More >

Ling Wang^1,2, Mohammad Faizuddin Md Noor^2,*, Yanan Zhang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084489 - 28 August 2026

Abstract Ultra-high-performance concrete (UHPC) relies on multivariable mix design and curing regimes, which makes empirical estimation of compressive strength increasingly unreliable when material systems vary. In this context, unlike previous studies that only applied standard eXtreme Gradient Boosting (XGBoost), this study introduces an advanced hybrid optimization strategy, Bayesian Optimization and Hyperband (BOHB), which combines the sample efficiency of Bayesian optimization with the resource allocation mechanism of Hyperband, and incorporates SHapley Additive exPlanations (SHAP) for influencing factor analysis, thereby proposing a BOHB-XGBoost framework integrated with SHAP analysis. The proposed model demonstrates excellent predictive accuracy and stability, achieving… More >

Abubaker Ahmed¹, Hosham Wahballa^2,*, AlaEldin Awouda³, Arafat Abdulgader Mohammed Elhag⁴, Ahmed Hamza Osman⁵, Mubarak Himmat⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084395 - 28 August 2026

Abstract Accurate force regulation is essential in robotic contact tasks such as polishing, grinding, and assembly. However, conventional impedance controllers often exhibit limited force-tracking accuracy, while adaptive methods require high tuning effort and computational cost. To address these issues, this paper proposes a Constant Impedance Force Controller (CIFC) based on a Force Reference Dependent Impedance (F_RDI) model, which is developed and validated through computer modeling and simulation. Robot environment interaction is computationally modeled as a mass damper spring system, and a position-based impedance framework is employed to regulate force deviations. A compensation signal derived from the F_RDI… More >

Hamza Rafik¹, Oussama Khouili², Mohamed Louzazni¹, Petru Adrian Cotfas³, Daniel Tudor Cotfas^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084256 - 28 August 2026

Abstract The rapid expansion of photovoltaic (PV) technologies has necessitated the enhancement of energy conversion efficiency by developing more and more sophisticated control and optimization techniques. In particular, novel MPPT methods combined with solar tracking systems and AI approaches emerge as a promising solution to surmount the barriers of the conventional PV systems. This research presents a critical assessment of the recent developments in the research area of PV systems with MPPT algorithms, solar tracking mechanisms, and AI-based techniques. Therefore, papers with publication years from 2021 to 2025 were selected using Web of Science Core Collection. More >

Hikmat Yar^1,2, Imran Ullah Khan³, Naqqash Dilshad⁴, Weiwei Jiang⁵, Heung Soo Kim^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084202 - 28 August 2026

Abstract Transportation has become an essential component of modern daily life, with continuous advancements aimed at reducing travel time and improving mobility. However, this increased convenience has also contributed to a rise in road accidents, often caused by driver distraction, fatigue, and age-related cognitive decline. These concerns have driven growing interest in Artificial Intelligence (AI)-based real-time driver monitoring systems designed to enhance road safety. Despite recent progress, several challenges remain, including limitations in detection accuracy, inadequate temporal reasoning, and high computational complexity. To address these challenges, we utilize the EfficientNetV2-S model for backbone feature extraction due… More >

Yih-Tzoo Chen¹, Thi-Hien Dao^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084193 - 28 August 2026

Abstract Construction strategy selection is a context-dependent decision problem in which multiple conflicting criteria must be considered under changing project conditions. Conventional multi-criteria decision-making (MCDM) methods generally produce rankings for predefined decision matrices but do not learn transferable preference structures across project scenarios. This study proposes a hybrid framework integrating T-spherical fuzzy sets, the Criteria Importance Through Intercriteria Correlation (CRITIC) method, the Combined Compromise Solution (CoCoSo) method, and RankNet-based pairwise learning. Fifty construction scenarios were designed using six contextual variables, and eight construction strategies were evaluated against eight criteria. Linguistic evaluations were transformed using a seven-level… More >

Kangjia Fan¹, Biao He^2,*, Shahab Hosseini³, Seyed Yaser Mousavi Siamakani^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084187 - 28 August 2026

Abstract Mining activities are associated with environmental side effects, which can be successfully predicted and strategies proposed for mitigating their adverse impacts. The cleaner production policies of green blasting focus on ecological issues related to mining operations and reduction plans. As a prediction part of this policy, this research proposed a mathematical model named Gene Expression Programming (GEP) to accurately predict the factors that generated pollutions, i.e., total suspended particles (TSP), particles dust with an analogous aerodynamic diameter of less than 10 μm (PM₁₀), and dust emission distance due to mine blasting (DEMB), simultaneously. As the reduction… More > Graphic Abstract

Jaeseung Lee¹, Jehyeok Rew^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.084165 - 28 August 2026

Abstract Accurate and interpretable fault diagnosis of electric vehicle (EV) powertrains is essential for ensuring operational safety, reliability, and efficient maintenance. Undetected faults in key components such as motors, inverters, and batteries can lead to performance degradation and critical system failures. While machine learning (ML)-based fault diagnosis models have demonstrated strong predictive capability using multivariate sensor data, their black-box nature limits practical trust and adoption in real-world EV applications. In particular, understanding how individual sensor variables contribute to diagnostic decisions remains a major challenge. To address this issue, this study proposes a novel interpretability method for… More >

Pengyu Wang¹, Tian Li¹, Jiye Zhang^1,*, Keyue Zhang², Jiawei Zhang^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.083990 - 28 August 2026

Abstract With the continuous expansion of rail transport capacity and the increasing speeds of freight trains, it has become increasingly common for passenger and freight trains to share the tracks on double-track or high-speed rail sections. To reveal the evolution of pressure wave characteristics during non-uniform-speed encounters between high-speed trains and freight trains on bridges, this study establishes a full-scale computational model of a steel truss flexible arch bridge and the conditions under which a train passes over it, with the bridge model serving solely as an aerodynamic boundary condition. The numerical simulation is based on… More >