High-efficiency Axial Flow Fan Design by Combining Through-flow Modeling, Optimization Algorithm and Computational Fluid Dynamics Simulation by C. Lee, S. W. Kim, H. T. Byun, S. H. Yang

“…The optimization algorithm is applied to the fan design and through-flow analysis program, achieving a very fast and simple optimization process and obtaining the optimal axial fan model. …”
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Advanced internet of things enhanced activity recognition for disability people using deep learning model with nature-inspired optimization algorithms by Mohammed Maray

“…The EARDP-DLMNOA model mainly relies on improving the activity recognition model using advanced optimization algorithms. …”
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An application of Arctic puffin optimization algorithm of a production model for selling price and green level dependent demand with interval uncertainty by Hachen Ali, Md. Al-Amin Khan, Ali Akbar Shaikh, Adel Fahad Alrasheedi, Seyedali Mirjalili

“…To assess the accuracy and reliability of the proposed model, the Arctic Puffin Optimization (APO) algorithm is employed to analyze and solve a specific numerical illustration. …”
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Design of Block-Scrambling-Based privacy protection mechanism in healthcare using fusion of transfer learning models with Hippopotamus optimization algorithm by Ghada Moh. Samir Elhessewi, Mohammed Yahya Alzahrani, Mohammad Alamgeer, Abdulbasit A. Darem, Da’ad Albalawneh, Mohammed Alqahtani, Mutasim Al Sadig, Sultan Alanazi

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Short-Term Power Load Prediction of VMD-LSTM Based on ISSA Optimization by Shuai Wu, Huafeng Cai

“…To address the challenges of fluctuating power loads and inaccurate predictions by conventional methods, this paper presents a novel hybrid framework combining Variational Mode Decomposition (VMD), Long Short-Term Memory (LSTM), and the Improved Sparrow Search Algorithm (ISSA). First, the power load series is decomposed into intrinsic mode functions (IMFs) via VMD, where the optimal decomposition order K is determined using permutation entropy (PE). …”
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Optimization Design of Flexible Net Capture System for Low, Slow, and Small Unmanned Aerial Vehicles Based on Improved Multi-Objective Wolf Pack Algorithm by Ran Xu, Qiang Peng, Husheng Wu

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Multiscale feature tuned trans-DeepLabV3+ based semantic segmentation of aerial images using improved red piranha optimization algorithm by P. Anilkumar, K. Lokesh, A. Naveen Kumar, D. John Pradeep, Y. V. Pavan Kumar, Rammohan Mallipeddi

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Iterative segmentation and classification for enhanced crop disease diagnosis using optimized hybrid U-Nets model by Malathi Chilakalapudi, Sheela Jayachandran

“…To further refine this model, classification is adeptly handled by a process inspired by the LeNet architecture, significantly improving identification against various diseases. …”
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An adaptive hierarchical hybrid kernel ELM optimized by aquila optimizer algorithm for bearing fault diagnosis by Hao Yan, Liangliang Shang, Wan Chen, Mengyao Jiang, Tianqi lu, Fei Li

“…The AO algorithm is further enhanced by incorporating chaos mapping, implementing a refined balanced search strategy, and fine-tuning parameter $$G_2$$ , which collectively improve its ability to escape local optima and conduct global searches, thus strengthening the robustness of the model during parameter optimization. …”
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Solving Integer Ambiguity Based on an Improved Ant Lion Algorithm by Wuzheng Guo, Yuanfa Ji, Xiyan Sun, Xizi Jia

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A Gradient-Based Optimization Algorithm for Optimal Control Problems With General Conformable Fractional Derivatives by Essia Ben Alaia, Slim Dhahri, Omar Naifar

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Nighttime Vehicle Detection Algorithm Based on Improved YOLOv7 by Fan Zhang

“…Ablation experiments verify the synergistic optimization effect and efficiency of each module. Furthermore, a comparison with other state-of-the-art algorithms like SSD and DETR confirms the superiority of our approach. …”
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Lithium-Ion Battery Health State Prediction Based on Improved War Optimization Assisted-Long and Short-Term Memory Network by Xiankun Wei, Mingli Mo, Silun Peng

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Time-Dependent Multi-Center Semi-Open Heterogeneous Fleet Path Optimization and Charging Strategy by Tingxin Wen, Haoting Meng

“…The self-organizing mapping network method is employed to initialize the EV routing, and an improved adaptive large neighborhood search (IALNS) algorithm is developed to solve the optimization problem. …”
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Automatic Brain Tumor Segmentation from MRI using Greedy Snake Model and Fuzzy C-Means Optimization by C. Jaspin Jeba Sheela, G. Suganthi

“…A mask is formed by thresholding the reconstructed image and is eroded to improve the accuracy of segmentation in Greedy Snake algorithm. …”
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An Improved Optimal Cloud Entropy Extension Cloud Model for the Risk Assessment of Soft Rock Tunnels in Fault Fracture Zones by Shuangqing Ma, Yongli Xie, Junling Qiu, Jinxing Lai, Hao Sun

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Prediction of the 180 day functional outcomes in aneurysmal subarachnoid hemorrhage using an optimized XGBoost model by Weichong Zhou, Xingfu Liao, Hui Shi, Mingfeng Wang, Yunchong Xiao, Xilu Yu, Yilong Wu, YanYi Liu, Yin Peng, Hai Su

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Fitness exercise evaluation system based on improved DTW algorithm by Tinghang Guo, Qianhan Yin, Xinlin Liu, Yue Sun, Zhuanping Qin, Yu Han, Guangda Lu

“…In addition, an improved dynamic time warping (S - WFDTW) algorithm is introduced. …”
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Lightweight insulator target detection algorithm based on improved YOLOX by Bing Zeng, Wei Hua, Dezhi Li, Zhihao Zhou, Hao Wan, Yunmin Xie, Tangbing Li, Yucong Chen, Jianglei Li, Shenli Wang, Shixun Fu, Zihan Jin, Wenhua Zhang

“…Additionally, Coordinate Attention (CA) is integrated into the detection head to improve the precision of small target detection. Finally, the σWIoU loss function replaces the traditional IoU to accelerate convergence and optimize overall performance. …”
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Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.) by Fazilat Fakhrzad, Warqaa Muhammed ShariffAl-Sheikh, Mohammed M. Mohammed, Heidar Meftahizadeh

“…Collectively, these findings highlight the potential of integrating machine learning and evolutionary optimization algorithms as powerful computational tools for crop improvement and agronomic decision-making.…”
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