Viet Tinh Nguyen, Rujira Chaysiri^*

Energy Engineering, Vol.122, No.2, pp. 515-536, 2025, DOI:10.32604/ee.2024.057786 - 31 January 2025

Abstract This paper presents a novel multi-criteria decision-making (MCDM) model for selecting optimal locations for a solar-wind hybrid energy plant in Vietnam. The study employs the Criteria Importance Through Intercriteria Correlation (CRITIC) and Combined Compromise Solution (CoCoSo) methods to address the challenge of evaluating potential sites based on a range of economic, technical, environmental, and social criteria. By integrating CRITIC for criteria weighting and CoCoSo for ranking alternatives, the study underscores the importance of objective, data-driven approaches in the strategic planning and implementation of sustainable energy projects. The results identify Ham Thuan Nam District in Binh More >

Mohammad Javad Bayat¹, Amin Kalhori², Kamran Asemi^1,*, Masoud Babaei³

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1351-1458, 2025, DOI:10.32604/cmes.2025.060222 - 27 January 2025

Abstract Since the initial observation of carbon nanotubes (CNTs) and graphene platelets (GPLs) in the 1990 and 2000s, the demand for high-performance structural applications and multifunctional materials has driven significant interest in composite structures reinforced with GPLs and CNTs. Incorporating these nanofillers into matrix materials markedly enhances the mechanical properties of the structures. To further improve efficiency and functionality, functionally graded (FG) distributions of CNTs and GPLs have been proposed. This study presents an extensive review of computational approaches developed to predict the global behavior of composite structural components enhanced with CNT and GPL nanofillers. The… More >

Nur Syahirah Wahid^1,*, Nor Ain Azeany Mohd Nasir^2,3, Norihan Md Arifin^1,3, Ioan Pop^4,5

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1865-1881, 2025, DOI:10.32604/cmes.2024.059508 - 27 January 2025

Abstract Modeling the boundary layer flow of ternary hybrid nanofluids is important for understanding and optimizing their thermal performance, particularly in applications where enhanced heat transfer and fluid dynamics are essential. This study numerically investigates the boundary layer flow of alumina-copper-silver/water nanofluid over a permeable stretching/shrinking sheet, incorporating both first and second-order velocity slip. The mathematical model is solved in MATLAB facilitated by the bvp4c function that employs the finite difference scheme and Lobatto IIIa formula. The solver successfully generates dual solutions for the model, and further analysis is conducted to assess their stability. The findings More >

Ching-Lung Fan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1995-2017, 2025, DOI:10.32604/cmes.2025.059414 - 27 January 2025

Abstract The construction phase of a project is a critical factor that significantly impacts its overall success. The construction environment is characterized by uncertainty and dynamism, involving nonlinear relationships among various factors that affect construction quality. This study utilized 987 construction inspection records from 1993 to 2022, obtained from the Taiwanese Public Construction Management Information System (PCMIS), to determine the relationships between construction factors and quality. First, fuzzy logic was applied to calculate the weights of 499 defects, and 25 critical construction factors were selected based on these weight values. Next, a deep neural network was… More >

Slim Chaoui^1,*, Omar Alruwaili¹, Faeiz Alserhani¹, Haifa Harrouch²

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1933-1954, 2025, DOI:10.32604/cmes.2025.059346 - 27 January 2025

Abstract In this paper, we propose a hybrid decode-and-forward and soft information relaying (HDFSIR) strategy to mitigate error propagation in coded cooperative communications. In the HDFSIR approach, the relay operates in decode-and-forward (DF) mode when it successfully decodes the received message; otherwise, it switches to soft information relaying (SIR) mode. The benefits of the DF and SIR forwarding strategies are combined to achieve better performance than deploying the DF or SIR strategy alone. Closed-form expressions for the outage probability and symbol error rate (SER) are derived for coded cooperative communication with HDFSIR and energy-harvesting relays. Additionally,… More >

Miloš Sedak^*, Maja Rosić, Božidar Rosić

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 2111-2145, 2025, DOI:10.32604/cmes.2025.059319 - 27 January 2025

Abstract This paper introduces a hybrid multi-objective optimization algorithm, designated HMODESFO, which amalgamates the exploratory prowess of Differential Evolution (DE) with the rapid convergence attributes of the Sailfish Optimization (SFO) algorithm. The primary objective is to address multi-objective optimization challenges within mechanical engineering, with a specific emphasis on planetary gearbox optimization. The algorithm is equipped with the ability to dynamically select the optimal mutation operator, contingent upon an adaptive normalized population spacing parameter. The efficacy of HMODESFO has been substantiated through rigorous validation against established industry benchmarks, including a suite of Zitzler-Deb-Thiele (ZDT) and Zeb-Thiele-Laumanns-Zitzler (DTLZ) More >

Moein Tosan¹, Mohammad Reza Gharib^2,*, Nasrin Fathollahzadeh Attar³, Ali Maroosi⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1109-1154, 2025, DOI:10.32604/cmes.2025.058595 - 27 January 2025

Abstract Accurate estimation of evapotranspiration (ET) is crucial for efficient water resource management, particularly in the face of climate change and increasing water scarcity. This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers, selected according to PRISMA guidelines, to evaluate the performance of Hybrid Artificial Neural Networks (HANNs) in ET estimation. The findings demonstrate that HANNs, particularly those combining Multilayer Perceptrons (MLPs), Recurrent Neural Networks (RNNs), and Convolutional Neural Networks (CNNs), are highly effective in capturing the complex nonlinear relationships and temporal dependencies characteristic of hydrological processes. These… More >

Muhammad Armghan Latif¹, Zohaib Mushtaq^2,*, Saifur Rahman³, Saad Arif⁴, Salim Nasar Faraj Mursal³, Muhammad Irfan³, Haris Aziz⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1667-1695, 2025, DOI:10.32604/cmes.2024.056850 - 27 January 2025

Abstract Ransomware attacks pose a significant threat to critical infrastructures, demanding robust detection mechanisms. This study introduces a hybrid model that combines vision transformer (ViT) and one-dimensional convolutional neural network (1DCNN) architectures to enhance ransomware detection capabilities. Addressing common challenges in ransomware detection, particularly dataset class imbalance, the synthetic minority oversampling technique (SMOTE) is employed to generate synthetic samples for minority class, thereby improving detection accuracy. The integration of ViT and 1DCNN through feature fusion enables the model to capture both global contextual and local sequential features, resulting in comprehensive ransomware classification. Tested on the UNSW-NB15 More >

Mohamed M. Kamara^1,*, Nora M. Al Aboud², Hameed Alsamadany³, Abeer M. Kutby⁴, Imen Ben Abdelmalek⁵, Diaa Abd El-Moneim⁶, Motrih Al-Mutiry⁷

Phyton-International Journal of Experimental Botany, Vol.94, No.1, pp. 101-122, 2025, DOI:10.32604/phyton.2025.058033 - 24 January 2025

Abstract Nitrogen (N) is a crucial nutrient vital for the growth and productivity of maize. However, excessive nitrogen application can result in numerous environmental and ecological problems, such as water pollution, biodiversity loss, and greenhouse gas emissions. Therefore, breeding maize hybrids resilient to low nitrogen conditions is crucial for sustainable agriculture, especially under low nitrogen conditions. Consequently, this study aimed to evaluate the combining ability and heterosis of maize lines, recognize promising hybrids, and study gene action controlling key traits under low and recommended N stress conditions. The half-diallel mating design hybridized seven maize inbreds, resulting… More >

Saeed Dinarvand^*, Amirmohammad Abbasi, Sogol Gharsi

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.1, pp. 37-60, 2025, DOI:10.32604/fdmp.2024.057545 - 24 January 2025

Abstract The present review explores the promising role of nanofluids and related hybrid variants in enhancing the efficiency of flat tube car radiators. As vehicles become more advanced and demand better thermal performance, traditional coolants are starting to fall short. Nanofluids, which involve tiny nanoparticles dispersed into standard cooling liquids, offer a new solution by significantly improving heat transfer capabilities. The article categorizes the different types of nanofluids (ranging from those based on metals and metal oxides to carbon materials and hybrid combinations) and examines their effects on the improvement of radiator performance. General consensus More >