Engineering Science and Technology-An International Journal-Jestech最新文献_第4页

Low-light image enhancement using autoencoder-based histogram matching 使用基于自编码器的直方图匹配的微光图像增强

IF 5.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-12-01 DOI: 10.1016/j.jestch.2025.102236

Serdar Çiftçi

Low-light image enhancement (LLIE) is a fundamental preprocessing task in computer vision which is essential for enhancing the quality and visibility of images that are captured under poor illumination. Traditional LLIE methods have lower computational costs but often lack to maintain natural tone distributions. In contrast, deep learning-based LLIE methods produce high-quality results at the cost of complex computations and significant training resources. This study introduces Autoencoder-Based Histogram Matching (AEHM), a hybrid LLIE framework that combines the effectiveness of the conventional histogram matching method with the representational capability of autoencoders. In AEHM, a pre-trained autoencoder predicts an optimal reference histogram from the low-light input image histogram, which is then used to perform histogram matching. Experiments conducted on multiple benchmark datasets demonstrate that AEHM outperforms traditional methods and delivers performance comparable to deep learning-based methods, while operating at a fraction of their computational costs, as measured by FLOPs. In particular, AEHM yields average improvements of about 2–3.5 dB in PSNR and 8%–12% in SSIM, together with a 30%–45% reduction in LPIPS, demonstrating its effectiveness in enhancing visual quality while preserving structural and perceptual fidelity.

弱光图像增强（LLIE）是计算机视觉中的一项基本预处理任务，对于提高在弱光条件下捕获的图像的质量和可见性至关重要。传统的LLIE方法计算成本较低，但往往不能保持自然的音调分布。相比之下，基于深度学习的LLIE方法以复杂的计算和大量的训练资源为代价产生高质量的结果。本研究引入了基于自编码器的直方图匹配（AEHM），这是一种混合LLIE框架，将传统直方图匹配方法的有效性与自编码器的表示能力相结合。在AEHM中，预训练的自编码器从低光输入图像直方图中预测最佳参考直方图，然后使用该直方图进行直方图匹配。在多个基准数据集上进行的实验表明，AEHM优于传统方法，其性能可与基于深度学习的方法相媲美，而计算成本（以FLOPs衡量）仅为传统方法的一小部分。特别是，AEHM的PSNR平均提高了2-3.5 dB， SSIM平均提高了8%-12%，LPIPS平均降低了30%-45%，证明了其在保持结构和感知保真度的同时提高视觉质量的有效性。

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引用次数: 0

MRAN-VQA: Multimodal Recursive Attention Network for Visual Question Answering MRAN-VQA：视觉问答的多模态递归注意网络

IF 5.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-12-01 DOI: 10.1016/j.jestch.2025.102232

Mohammad Shariful Islam , Mohammad Abu Tareq Rony , Md Murad Hossain Sarker , Md. Khairul Bashar Bhuiyan , Md Saib , Md. Aktarujjaman , Md Shahab Uddin , Abeer D. Algarni , Ahmad Taher Azar , Walid El-Shafai

Visual Question Answering (VQA) is a fundamental challenge in multimodal AI, requiring models to integrate and reason over both visual and textual information. Despite advancements in deep learning, existing VQA models struggle with multi-step reasoning, hierarchical feature fusion, and multilingual generalization, limiting their effectiveness in real-world applications. This paper introduces MRAN-VQA, a Multimodal Recursive Attention Network for VQA, designed to address these limitations through a three-stage reasoning pipeline. The proposed approach first employs Recursive Attention Encoding, where a Vision Transformer (ViT) extracts visual features, and BERT-based embeddings encode textual information. A recursive self-attention mechanism iteratively refines these representations, improving contextual alignment. Hierarchical Feature Fusion integrates multi-level visual–text interactions through bilinear attention pooling and gated cross-modal operations. Finally, Answer Prediction with Attention Grounding applies a self-attentive reasoning module to responses while optimizing an Attention Grounding Score (AGS) for improved interpretability. Experiments on VQA v2.0, CLEVR, and our custom BanglaVQA datasets demonstrate that MRAN-VQA outperforms state-of-the-art models, achieving 75.6% accuracy on VQA v2.0, 96.1% on CLEVR, and 72% on BanglaVQA—notably surpassing transformer-based baselines. The model exhibits superior multi-step reasoning capabilities in compositional queries and significantly enhances performance in low-resource multilingual settings.

视觉问答（VQA）是多模态人工智能的一个基本挑战，它要求模型对视觉和文本信息进行整合和推理。尽管深度学习取得了进步，但现有的VQA模型在多步推理、分层特征融合和多语言泛化方面存在困难，限制了它们在实际应用中的有效性。本文介绍了MRAN-VQA，一种用于VQA的多模态递归注意力网络，旨在通过三阶段推理管道解决这些限制。该方法首先采用递归注意编码，其中视觉转换器（ViT）提取视觉特征，基于bert的嵌入编码文本信息。递归的自注意机制迭代地细化这些表示，提高上下文一致性。分层特征融合通过双线性注意力池和门控跨模态操作集成了多层次的视觉-文本交互。最后，基于注意基础的答案预测在优化注意基础分数（AGS）以提高可解释性的同时，对答案应用自关注推理模块。在VQA v2.0、CLEVR和我们定制的BanglaVQA数据集上的实验表明，MRAN-VQA优于最先进的模型，在VQA v2.0上达到75.6%的准确率，在CLEVR上达到96.1%，在BanglaVQA上达到72%——明显超过了基于变压器的基线。该模型在组合查询中表现出优越的多步推理能力，并显著提高了低资源多语言设置的性能。

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引用次数: 0

Ultra-wideband EMP-shielded glass windows using metal mesh films for civilian and military infrastructure 民用和军用基础设施用金属网薄膜的超宽带电磁屏蔽玻璃窗

IF 5.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-12-01 DOI: 10.1016/j.jestch.2025.102235

Dat Tien Nguyen , Keunsik No , Chang Won Jung

A hybrid window structure integrated with metal mesh films (MMFs) is proposed for electromagnetic pulse (EMP) protection in both civilian and military applications. The structure operates over an ultra-wide frequency range from 0.18 to 18 GHz. To the best of our knowledge, research on EMP-shielding windows remains limited in terms of frequency coverage, shielding effectiveness (SE), and optical transparency (OT), with most studies focusing on electromagnetic interference (EMI) shielding windows that achieve SE < 80 dB. This work presents four EMP shielding window configurations, each achieving SE > 80 dB and incorporating, for the first time, an asymmetric hexagonal mesh design. The metal mesh, deposited on a transparent dielectric substrate, exhibits OT of 75.5 % and a sheet resistance of 0.1 Ω/□. Compared to conventional square and symmetric hexagonal meshes, the asymmetric mesh improves SE by up to 4.7 dB at 10 GHz, with only a slight reduction in OT of about 3 %, demonstrating a superior balance between electromagnetic performance and transparency. Four window configurations are examined through both simulation and measurement, with square meshes from our previous work included for comparison. For civilian applications, double-pane glass with two MMF layers achieves average SE above 60 dB while maintaining OT over 40 %. For military applications, three-layer structures reach SE up to 90 dB with OT above 30 %. These results confirm that the proposed configurations provide broadband EMP shielding with sufficient transparency, offering a practical and scalable solution for EMP SE windows.

提出了一种结合金属网膜（MMFs）的混合窗口结构，用于民用和军用电磁脉冲防护。该结构在0.18至18 GHz的超宽频率范围内工作。据我们所知，对电磁屏蔽窗口的研究在频率覆盖、屏蔽效能（SE）和光透明度（OT）方面仍然有限，大多数研究集中在SE达到80 dB的电磁干扰（EMI）屏蔽窗口上。这项工作提出了四种EMP屏蔽窗口配置，每种配置均达到SE >； 80 dB，并首次采用非对称六边形网格设计。该金属网沉积在透明介质基板上，OT为75.5%，片电阻为0.1 Ω/□。与传统的方形和对称六角形网格相比，非对称网格在10 GHz时将SE提高了4.7 dB，而OT仅略微降低了约3%，证明了电磁性能和透明度之间的卓越平衡。通过模拟和测量检查了四种窗口配置，其中包括我们以前工作中的方形网格进行比较。对于民用应用，两层MMF双层玻璃的平均SE高于60 dB，同时OT保持在40%以上。对于军事应用，三层结构的SE高达90 dB， OT高于30%。这些结果证实，所提出的配置提供了宽带EMP屏蔽，具有足够的透明度，为EMP SE窗口提供了实用且可扩展的解决方案。

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引用次数: 0

Air side thermal and hydraulic performance assessment of skived, louver, offset honeycomb, and metal foam finned mini-channel heat exchangers 楔形，百叶，偏移蜂窝和金属泡沫翅片微型通道热交换器的空气侧热和水力性能评估

IF 5.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-12-01 DOI: 10.1016/j.jestch.2025.102242

Bahadır Doğan , M. Mete Ozturk , Levent Turhan

This study presents a comparative performance evaluation of mini-channel compact heat exchangers, focusing on four distinct extended surface configurations of skived plate fin, louver fin, metal foam, and offset honeycomb. The experiments are conducted in an air tunnel, where the Re number of the airflow ranges from 100–1400, and a constant surface temperature is maintained using a water bath. To ensure a fair comparison, all four configurations are tested under identical conditions. The performance of each configuration is assessed in terms of air-side heat transfer coefficient, pressure drop, Colburn j-factor, and friction factor. In addition to these conventional performance indicators, the heat exchangers are further evaluated using the heat transfer index with respect to friction power, both with and without accounting for compactness. According to the findings, although the cell-based configurations consistently outperform the plate-fin configurations under all conditions, the metal foam and offset honeycomb each demonstrate superiority in different performance metrics. While the heat transfer coefficient reaches approximately 110 W/(m²K) for the metal foam configuration, the offset honeycomb achieves up to 100 W/(m²K) within the same flow range. When evaluated based on the heat transfer index considering compactness, the performance order shifts, with offset honeycomb and metal foam providing values of 60.08 kW/(m³K) and 56.76 kW/(m³K), respectively. Under all tested conditions, the louver configuration, although the most commonly utilized extended surface in conventional applications, falls short of achieving the performance levels demonstrated by the novel designs introduced in this study.

本研究对小型通道紧凑型热交换器的性能进行了比较评估，重点研究了四种不同的扩展表面结构：刨花板翅片、百叶翅片、金属泡沫和偏移蜂窝。实验在风洞中进行，气流的雷诺数在100-1400之间，用水浴保持表面温度恒定。为了确保公平的比较，在相同的条件下测试了所有四种配置。根据空气侧传热系数、压降、科尔伯恩j系数和摩擦系数来评估每种配置的性能。除了这些常规的性能指标外，热交换器还使用与摩擦功率有关的传热指标进行进一步评估，包括考虑和不考虑紧凑性。根据研究结果，尽管基于单元的配置在所有条件下都优于板鳍配置，但金属泡沫和偏移蜂窝在不同的性能指标上都表现出优势。金属泡沫结构的传热系数约为110 W/(m2K)，而偏移蜂窝在相同流量范围内的传热系数可达100 W/(m2K)。当考虑紧凑性的传热指数时，性能顺序发生变化，偏移蜂窝和金属泡沫的值分别为60.08 kW/(m3K)和56.76 kW/(m3K)。在所有测试条件下，百叶窗配置，虽然在传统应用中最常用的扩展表面，未能达到本研究中介绍的新设计所展示的性能水平。

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引用次数: 0

Novel multi-functional and compact waveguide filter based on various meta-resonators for C-band applications c波段应用中基于各种元谐振器的新型多功能紧凑波导滤波器

IF 5.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-12-01 DOI: 10.1016/j.jestch.2025.102213

Abdullah Genc , Habib Dogan

This paper presents the design, fabrication, and performance analysis of a novel, multi-functional WGF for C-band (4.90–7.05 GHz) applications. The novel WR-159 WG structure is precisely fabricated from Al6065 material by the CNC milling method, and also meta-resonator structures designed in different sizes and geometries are fabricated from low-loss Duroid/RT 5880 substrate material with help of LPKF. Thanks to the designed single WR-159 WG structure, the WGF with four different functions is experimentally realized using a set of meta-resonators that can be mounted and dismounted. These four functions are bandpass/bandstop, narrow/medium/wide bandwidth, shifting operating frequency (5.5, 6, and 6.5 GHz), and filter order (n = 1–7). Filter performance has been verified through simulations and measurements with a vector network analyzer (VNA). For each WGF designed for different functions, simulated and measured performance results, such as for center frequency (f₀), return loss (RL), insertion loss (IL), fractional bandwidth (FBW), and quality factor (Q) are compared, and they have good agreement with each other. The proposed modular structure offers a low-cost and versatile alternative that can replace commercial filters.

本文介绍了一种用于c波段（4.90-7.05 GHz）应用的新型多功能WGF的设计、制造和性能分析。以Al6065材料为基材，采用数控铣削的方法精确制备了新型WR-159元谐振腔结构，并在乐普科的帮助下，以低损耗Duroid/RT 5880基材制作了不同尺寸和几何形状的元谐振腔结构。利用设计的WR-159单模谐振器结构，利用一组可安装和拆卸的元谐振器，实验实现了具有四种不同功能的WGF。这四个功能是带通/带阻、窄/中/宽带宽、移位工作频率（5.5、6和6.5 GHz）和滤波器阶数（n = 1-7）。通过矢量网络分析仪（VNA）的仿真和测量，验证了滤波器的性能。针对不同功能设计的WGF，比较了中心频率（f0）、回波损耗（RL）、插入损耗（IL）、分数带宽（FBW）、质量因子(Q)等性能的仿真和实测结果，结果吻合较好。所提出的模块化结构提供了一种低成本和多功能的替代方案，可以取代商用过滤器。

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引用次数: 0

Investigation of structural behavior in natural and synthetic fiber reinforced multilayer composites based on resin and additives 基于树脂和添加剂的天然和合成纤维增强多层复合材料的结构性能研究

IF 5.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-12-01 DOI: 10.1016/j.jestch.2025.102240

Samet Karabulut, Kaan Kaysadı, Faruk Gümüş

In our study, jute natural fiber and glass fiber were preferred as reinforcing elements. Epoxy, vinyl ester, and polyester were selected as matrix materials, and sodium hydroxide and magnesium hydroxide were used as additives. When the results were analyzed, the samples produced with epoxy yielded good results in tensile and elongation tests compared to the others, while the average values remained the same in bending and impact tests. The presence of additives was also observed in the SEM images and EDS results.

在我们的研究中，首选黄麻天然纤维和玻璃纤维作为增强元素。以环氧树脂、乙烯基酯和聚酯为基体材料，以氢氧化钠和氢氧化镁为助剂。结果分析表明，与其他样品相比，环氧树脂样品在拉伸和延伸试验中取得了良好的结果，而在弯曲和冲击试验中平均值保持不变。在SEM图像和EDS结果中也观察到添加剂的存在。

引用次数: 0

Linear Doherty power amplifier design based on adaptive input signal power control 基于自适应输入信号功率控制的线性多尔蒂功率放大器设计

IF 5.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-12-01 DOI: 10.1016/j.jestch.2025.102247

Zhiqing Liu , Ye Zhong , Zhijiang Dai

In modern wireless communication systems, the trade-off between efficiency and linearity in Doherty power amplifiers (DPAs) remains a critical challenge. To address this, a novel Schottky diode-based input matching network is presented for peaking power amplifiers (PAs) which leverages a dual optimization mechanism: (1) adaptive gate DC bias adjustment via Schottky rectification, enabling Class B operation in high-power regions to enhance DPA linearity; and (2) nonlinear impedance modulation to suppress premature peaking PA activation in low-power regions, thereby improving back-off efficiency. Based on this structure, an asymmetric DPA is designed and manufactured, with continuous wave test results showing that saturation efficiency is higher than 50%, saturated output power reaches more than 43.4 dBm, and the back-off efficiency of 9 dB is 41.2%–55.6% in the operating band of 0.75–1.25 GHz. The adjacent channel power ratio (ACPR) of the PA is tested using a 20 MHz quadrature amplitude modulation (QAM) signal with a PAPR of 9 dB, and the test results show that, in the band of 1.0–1.3 GHz, the ACPR is −38.1 to −34.0 dBc and average efficiency is from 34.2%–45.5% at an average output power of 36 dBm, which verifies that the designed DPA has good linearity performance.

在现代无线通信系统中，Doherty功率放大器（dpa）的效率和线性度之间的权衡仍然是一个关键的挑战。为了解决这个问题，提出了一种新的基于肖特基二极管的峰值功率放大器（pa）输入匹配网络，该网络利用双重优化机制：(1)通过肖特基整流自适应栅极直流偏置调整，使B类工作在高功率区域，提高DPA线性度；(2)非线性阻抗调制，抑制低功率区域PA的过早峰值激活，从而提高退退效率。基于该结构设计并制造了非对称DPA，连续波测试结果表明，在0.75 ~ 1.25 GHz工作频段，饱和效率高于50%，饱和输出功率大于43.4 dBm， 9db的回退效率为41.2% ~ 55.6%。采用PAPR为9 dB的20 MHz正交调幅（QAM）信号对该放大器的邻道功率比（ACPR）进行了测试，测试结果表明，在1.0 ~ 1.3 GHz频段，平均输出功率为36 dBm时，ACPR为−38.1 ~−34.0 dBc，平均效率为34.2% ~ 45.5%，验证了所设计的DPA具有良好的线性性能。

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引用次数: 0

Optimization of pin-fin arrangement in traction inverter cooling systems: A framework based on CFD simulations, deep neural networks and evolutionary algorithms 牵引式逆变器冷却系统翅片排列优化：基于CFD仿真、深度神经网络和进化算法的框架

IF 5.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-11-21 DOI: 10.1016/j.jestch.2025.102238

Luca Donetti , Gaetano Patti , Stefano Mauro , Gaetano Sequenzia , Michele Calabretta

Efficient thermal management is essential for the reliability and performance of traction inverters. However, direct optimization via Computational Fluid Dynamics (CFD) is often impractical due to the high dimensionality of the design space and the high computational cost of each simulation. To overcome this limitation, a surrogate-based optimization framework is developed to enhance the thermal and hydraulic performance of an automotive traction inverter cooling system. The methodology integrates CFD, deep neural networks (DNNs), and a multi-objective evolutionary algorithm. A simplified representation of the ACEPACK^TM DRIVE power module is employed to generate an extensive dataset through automated, GPU-accelerated CFD simulations, making data generation computationally feasible while avoiding the prohibitive cost of direct optimization. A DNN surrogate model is trained to accurately predict pressure drop and heated-wall temperature, achieving mean relative errors below 3% and 1%, respectively. This surrogate model then guides a Non-Dominated Sorting Genetic Algorithm III in the optimization of key geometric parameters, including pin-fin diameter, spacing, height, wall clearance, as well as of physical parameter such as the surface roughness of the pin-fins. CFD-based validation of the Pareto-optimal designs, performed on the full inverter geometry, indicates reductions of up to 25% in pressure drop and approximately 2% in junction temperature. These results suggest that the proposed methodology promises robustness and generalizability, showing good potential for further application in data-driven thermal design optimization.

高效的热管理对牵引逆变器的可靠性和性能至关重要。然而，由于设计空间的高维性和每次模拟的高计算成本，通过计算流体动力学（CFD）直接优化通常是不切实际的。为了克服这一限制，开发了一种基于代理的优化框架，以提高汽车牵引逆变器冷却系统的热工性能。该方法集成了CFD、深度神经网络（dnn）和多目标进化算法。采用ACEPACKTM DRIVE电源模块的简化表示，通过自动化的gpu加速CFD模拟生成广泛的数据集，使数据生成在计算上可行，同时避免了直接优化的高昂成本。通过训练DNN代理模型，可以准确预测压降和热壁温度，平均相对误差分别低于3%和1%。然后，该代理模型指导非支配排序遗传算法III优化关键几何参数，包括钉片直径、间距、高度、壁面间隙以及钉片表面粗糙度等物理参数。基于cfd的pareto优化设计验证，在整个逆变器几何结构上进行，表明压降降低高达25%，结温降低约2%。这些结果表明，所提出的方法具有鲁棒性和通用性，在数据驱动的热设计优化中具有良好的应用潜力。

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引用次数: 0

A novel mixed Rayleigh distribution model using PID based search algorithm for wind energy applications 基于PID搜索算法的混合瑞利分布模型在风能应用中的应用

IF 5.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-11-21 DOI: 10.1016/j.jestch.2025.102239

Hilmi Aygün , Bayram Köse

Accurate modeling of wind speed distributions is a critical prerequisite for reliable wind energy assessment, system optimization, and long-term performance prediction. Conventional probability distribution functions exhibit notable deviations between the observed and estimated wind speed frequency distributions, indicating their limited capability in capturing the actual variability of wind regimes. To address this gap, this study introduces, for the first time in the wind energy domain, the application of a Mixed Rayleigh distribution in combination with a PID-based metaheuristic optimization algorithm (PSA) for parameter estimation. The proposed approach was tested at three measurement stations: Karaburun, Mersinkoy, and Gelibolu, using extensive wind speed datasets. Comparative analyses were conducted between PSA based Rayleigh, Mixed Rayleigh, and Weibull models, alongside conventional Moment and Maximum Likelihood methods. The proposed model achieved the lowest Sum Square Error (SSE) (0.0016) and Root Mean Square Error (RMSE) (0.0091) in Karaburun, the lowest SSE (0.0014) and RMSE (0.0075) in Gelibolu, and consistently high determination coefficients (R² ≈ 0.9999) across all regions. Additionally, the model yielded the lowest Mean Absolute Percentage Error (MAPE) based on Wind Power Density (WPD) (4.11 %) in Mersinköy and relatively low MAPE values based on Average Wind Speed (3.74 % and 3.26 %) in Karaburun and Mersinköy, respectively. In particular, the Mixed Rayleigh model demonstrated superior flexibility, resulting in improved fitting accuracy and reduced estimation errors. Overall, the findings highlight the methodological novelty and practical potential of combining hybrid distribution functions with advanced optimization algorithms.

风速分布的准确建模是可靠的风能评估、系统优化和长期性能预测的关键先决条件。传统的概率分布函数在观测到的风速频率分布和估计的风速频率分布之间存在显著的偏差，表明它们在捕捉风况的实际变异性方面的能力有限。为了解决这一差距，本研究首次在风能领域引入了混合瑞利分布与基于pid的元启发式优化算法（PSA）相结合的参数估计应用。该方法在Karaburun、Mersinkoy和Gelibolu三个观测站进行了测试，使用了大量的风速数据集。在基于PSA的瑞利、混合瑞利和威布尔模型以及传统的矩和最大似然方法之间进行了比较分析。该模型在卡拉布润的和方误差（SSE）（0.0016）和均方根误差（RMSE）（0.0091）最低，在格里博卢的SSE（0.0014）和均方根误差（RMSE）（0.0075）最低，并且在所有地区都具有较高的决定系数（R2≈0.9999）。此外，该模型基于风力密度（WPD）的平均绝对百分比误差（MAPE）在Mersinköy最低（4.11%），而基于平均风速的MAPE值在卡拉布伦和Mersinköy相对较低（3.74%和3.26%）。特别是，混合瑞利模型显示出优越的灵活性，从而提高了拟合精度，减少了估计误差。总的来说，这些发现突出了将混合分布函数与先进的优化算法相结合的方法的新颖性和实际潜力。

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引用次数: 0

DC-PFL: A dynamic clustering-based personalized federated learning method for human activity recognition DC-PFL：一种基于动态聚类的人类活动识别个性化联邦学习方法

IF 5.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-11-20 DOI: 10.1016/j.jestch.2025.102230

Xiaoxu Wen , Yan Wang , Menghao Yuan , Aihui Wang , Ge Zheng , Hongnian Yu , Lin Meng

Human Activity Recognition (HAR) is essential in pervasive computing, healthcare, and human–computer interaction, where accurate interpretation of motion data underpins intelligent decision-making. Federated Learning (FL) enables privacy-preserving model training across distributed clients without sharing raw data, but suffers from degraded performance under Non-Independent and Identically Distributed (Non-IID) data, a common challenge in HAR due to user diversity and device heterogeneity. To address this, Personalized Federated Learning (PFL) introduces client-specific modeling, often via clustering. However, most existing approaches adopt static clustering strategies, lacking adaptability to dynamic changes in client data distributions. In this work, we propose DC-PFL, a Dynamic Clustering-based Personalized Federated Learning framework that performs round-wise client clustering using lightweight statistical features, like Average Peak Frequency (APF), percentiles, and Median Absolute Deviation (MAD) derived from local model parameters. This design ensures efficient and privacy-preserving similarity estimation across clients. By dynamically adjusting clusters during training, DC-PFL enables fine-grained personalization, better generalization, and improved robustness to Non-IID conditions. Experimental results on HAR benchmarks demonstrate that DC-PFL achieves superior performance in both accuracy and convergence speed compared to existing methods, including FedCHAR and standard FL baselines, validating its effectiveness in real-world federated HAR scenarios.

人类活动识别（HAR）在普适计算、医疗保健和人机交互中是必不可少的，在这些领域，对运动数据的准确解释是智能决策的基础。联邦学习（FL）支持在不共享原始数据的情况下跨分布式客户端进行隐私保护模型训练，但在非独立和同分布（Non-IID）数据下性能下降，这是HAR中由于用户多样性和设备异构性而面临的常见挑战。为了解决这个问题，个性化联邦学习（PFL）通常通过集群引入了特定于客户端的建模。然而，大多数现有方法采用静态聚类策略，缺乏对客户机数据分布动态变化的适应性。在这项工作中，我们提出了DC-PFL，这是一个基于动态聚类的个性化联邦学习框架，它使用轻量级统计特征（如平均峰值频率（APF），百分位数和中位数绝对偏差（MAD））来执行round-wise客户端聚类。这种设计确保了客户端之间高效且保护隐私的相似性估计。通过在训练过程中动态调整聚类，DC-PFL可以实现细粒度个性化、更好的泛化，并提高对非iid条件的鲁棒性。HAR基准测试的实验结果表明，与现有方法（包括FedCHAR和标准FL基线）相比，DC-PFL在精度和收敛速度方面都具有优越的性能，验证了其在真实联邦HAR场景中的有效性。

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引用次数: 0