Estimating the Aboveground Biomass of an Evergreen Broadleaf Forest in Xuan Lien Nature Reserve, Thanh Hoa, Vietnam, Using SPOT-6 Data and the Random Forest Algorithm by The Dung Nguyen, Martin Kappas

“…Adding texture features into the predictor variables did not improve the model performance. In addition, the SPOT-6 sensor has the potential to predict forest AGB using the RF algorithm.…”
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Clustering analysis of Yue opera character tone trends based on quantum particle swarm optimization for fuzzy C-means. by Yuhang Zhang, Xiaofeng Wu, Jiawei Xu, Zihao Ning, Xiao Han

“…We designed a detection algorithm using trend data to validate our clustering method, thereby enhancing the accuracy of the analysis of tonal ranges and potential models. …”
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IHDETBO: A Novel Optimization Method of Multi-Batch Subtasks Parallel-Hybrid Execution Cloud Service Composition for Cloud Manufacturing by Li-Nan Zhu, Peng-Hang Li, Xiao-Long Zhou

“…To address the problem, a novel optimization method named as Improved Hybrid Differential Evolution and Teaching Based Optimization (IHDETBO) is proposed and introduced in detail. …”
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Refining efficiency in standalone proton exchange membrane fuel cell systems through gross hopper optimization-based maximum power point tracking control by Nethra K., Reddy K. Jyotheeswara, Dash Ritesh, Parida Prasanta Kumar, Swain Sarat Chandra, Dhanamjayulu C., Mahapatro Abinash

“…To further improve prediction accuracy, the GHO algorithm incorporates a natural cubic-spline prediction model within its iterative mechanism, which enhances power generation predictions under dynamic conditions such as abrupt changes in fuel cell temperature and reactant partial pressure. …”
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An Optimal Energy Management Strategy With Time-Varying Equivalent Factor Based on Transformer for Multi-Mode Hybrid Electric Mining Trucks by Xinxin Zhao, Jiaqi Li, Menglei Liu, Jinggang Zhang, Nasser Lashgarian Azad

“…This paper introduces an advanced Transformer network model aimed at an adaptive Energy Management Strategy (EMS) to improve the fuel efficiency of Hybrid Electric Mining Trucks (HEMTs). …”
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Parameter Optimization and Bending Performance Analysis of a Corrugated Steel Plate-UHPC Composite Bridge Deck with PZ Shear Connectors by Anhua Wang, Xiaobo Zheng, Wei Hou, Shuanhai He

“…This paper presents a methodology to optimize the parameters and mechanical performance of a corrugated steel plate-ultrahigh-performance concrete (UHPC) composite bridge deck with panel zone (PZ) shear connectors using the improved non-dominated sorting genetic algorithm (NSGA-II). …”
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Power Adaptation for Optimizing Secrecy Energy Efficiency in NOMA-Enabled Underlay Cognitive Radio Networks and DNN-Based Evaluation by P. P. Hema, A. V. Babu

“…The combination of Non-orthogonal multiple access (NOMA) and cognitive radio (CR) has become a reliable solution for improving spectrum efficiency in wireless networks. …”
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Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Saleh Ba-swaimi, Renuga Verayiah, Vigna K. Ramachandaramurthy, Ahmad K. ALAhmad, Sanjeevikumar Padmanaban

“…This work presents a stochastic two-stage mixed-integer nonlinear programming (MINLP) optimization model for the long-term planning of a distribution system (DS) to improve renewable energy integration over a ten-year period. …”
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Enhancing retail operations: Dynamic fulfilment strategies in Omnichannel retail by Hümeysa İskender, Sinem Dayanıklı, Abdullah Hulusi Kökçam, Željko Stević, Safiye Turgay, Mahmut Baydaş, Jasmina Bunevska Talevska

“…This study explores the trend of in-store fulfillment in omnichannel retail, where nearby store inventories are utilized for online order fulfillment. This model presents advantages such as faster delivery, cost reduction, improved stock management, increased sales, and enhanced customer satisfaction. …”
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Construction and scheduling optimization of renewable energy consumption forecasting system for twisted tire porcelain manufacturing industry based on deep learning by Fangrong Liao, Runlin Ran, Jiayi Zhang

“…After the algorithm is trained on GPU many times, the obtained optimal model is tested many times in the above data set, with an accuracy rate of 90.2% and a speed of 66 frames per second. …”
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SGDO-SLAM: A Semantic RGB-D SLAM System with Coarse-to-Fine Dynamic Rejection and Static Weighted Optimization by Qiming Hu, Shuwen Wang, Nanxing Chen, Wei Li, Jiayu Yuan, Enhui Zheng, Guirong Wang, Weimin Chen

“…Vision sensor-based simultaneous localization and mapping (SLAM) systems are essential for mobile robots to locate and generate spatial models of their surroundings. However, the majority of visual SLAM systems assume static settings, leading to significant accuracy degradation in dynamic scenes. …”
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A hybrid simple exponential smoothing-barnacles mating optimization approach for parameter estimation: Enhancing COVID-19 forecasting in Malaysia by Azlan Abdul Aziz, Zuriani Mustaffa, Suzilah Ismail, Nor Azriani Mohamad Nor, Nurin Qistina Mohamad Fozi

“…Therefore, this study aims to propose a new hybrid model, the Single Exponential Smoothing (SES)-Barnacles Mating Optimization (BMO) algorithm, to estimate the optimal smoothing parameter alpha and initial value that can improve the percentage of forecast accuracy. …”
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Enhancing Route Optimization in Road Transport Systems Through Machine Learning: A Case Study of the Dakhla-Paris Corridor by Najib El Karkouri, Lahcen Hassine, Younes Ledmaoui, Hasna Chaibi, Rachid Saadane, Nourddine Enneya, Mohamed El Aroussi

“…The study relies on applying advanced mathematical modeling techniques and analyzing several datasets to train various machine learning algorithms. …”
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Optimizing the core loading pattern and fuel composition in a hexagonal small modular nuclear reactor via ANN-PSO approach by G.R. Ansarifar, M.R. Karimi, H. Zayermohammadi Rishehri

“…The best model, based on TCs and PPFs, was selected. The analysis findings revealed significant improvements in safety parameters such as TCs and PPFs for optimal core loading pattern with optimized gadolinia (Gd2O3) Concentration.…”
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High-speed threat detection in 5G SDN with particle swarm optimizer integrated GRU-driven generative adversarial network by R. Shameli, Sujatha Rajkumar

“…The PSO optimizes the network weight of the GAN model to improve the backpropagation while generating the synthetic data (attack data) in the generator model using GRU. …”
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Research on the Performance Optimization of Turbulent Self-Noise Suppression and Sound Transmission of Acoustic Windows Made from Functionally Graded Material by Bing LI, Fu-Lin ZHOU, Jun FAN, Bin WANG, Liwen TAN

“…For a simplified sonar dome model, an optimization method for internal gradients of functionally graded material (FGM) acoustic windows is proposed in this paper. …”
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Dynamic Gesture Recognition and Interaction of Monocular Camera Based on Deep Learning by SUNBo wen, YU Feng

“…Through convolution and fullconnected network structure, as well as optimization of parameter selection and prevention of overfitting, combined with fingertip detection and elimination algorithm, the recognition accuracy is improved. …”
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Current Stress Optimization in Buck-Boost Mode Based on New Extended Phase-Shift Dual Active Full-Bridge Converter by TAO Haijun, WANG Hongyi, YANG Naitong

“…According to the relationship between the phase shift angles, working modes are divided into three types, and the current stress expression and power model are obtained. Moreover, the improved working mode is obtained by comparative analysis, and the optimal phase shift combination of current stress is obtained by using Lagrange multipler method algorithm. …”
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Distributed Robust Low-Carbon Economic Dispatch of Power Systems Considering Extreme Scenarios by HU Heng, QIN Jianru, LI Haibo, LIU Jiefeng

“…[Results] Case studies on an improved IEEE 39-node system using the column-and-constraint generation （C&CG） algorithm demonstrate that， compared with traditional deterministic and DRO models based on typical scenarios， the proposed approach increases scheduling costs by 7.11% and 14.37% respectively， but reduces renewable curtailment rates by 8.28% and 34.65%， and load shedding rates by 8.19% and 33.32%. …”
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RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

“…The graphs are processed using a graph neural network with DiffPool. To optimize feature integration, we incorporate an improved dung beetle optimization algorithm, which adaptively assigns fusion weights during inference. …”
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