An enhanced moth flame optimization extreme learning machines hybrid model for predicting CO2 emissions by Ahmed Ramdan Almaqtouf Algwil, Wagdi M. S. Khalifa

“…GMSMFO enhances population diversity and avoids local optima through Gaussian mutation (GM), while the shrink mechanism (SM) improves exploration–exploitation balance. Validated on the congress on evolutionary computation (CEC2020) benchmark suite (dimensions 30 and 50), GMSMFO demonstrated superior performance compared to other optimization algorithms. …”
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Study on the parameters of the matrix NTRU cryptosystem by LI Zichen, WU Qinghao, SONG Jiashuo, PENG Haipeng

“…With the rapid development of quantum computers， post-quantum cryptography has emerged as a prominent area of research in cryptography.ObjectivesIn order to avoid the decryption failure in matrix NTRU as NTRU， the Matrix NTRU algorithm was optimized.MethodsBased on the method of constraining the parameter space in congruent cryptographic algorithms， a method for optimal selection of the parameter space of matrix NTRU cryptographic regimes was proposed. …”
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Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model by Guowei Li, Gang Tang, Jingyu Zhang, Qun Sun, Xiangjun Liu

“…The data show that the optimized root mean square error (RMSE) value under level 5 sea conditions is 0.01265 compared to 0.01673 before optimization, and the optimized RMSE value under level 6 sea conditions is 0.01140 compared to 0.01479 before optimization, which demonstrates that the error between the predicted value and the actual value of the model decreases. …”
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Cross-Domain Edge Computing Offloading Strategy for Delay-Optimized in Low Earth Orbit Satellite Network by YANG Guisong, HUANG Yechao, HE Xingyu

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RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

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Energy Efficiency Optimization for UAV Distribution and Resource Allocation in NOMA and Multi-UAV Assisted Wireless Networks by Yuan Ren, Jieyu Wang, Yulong Xiao, Xuewei Zhang, Fan Jiang, Junxuan Wang, Jing Jiang, Guangyue Lu

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A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements by Zheng Zeng, Linkai Tao, Hangyu Zhu, Yunfeng Zhu, Long Meng, Jiahao Fan, Chen Chen, Wei Chen

“…Methods and procedures: To select the optimum channels and relevant features, and eliminate irrelevant information, a heuristical search algorithm (i.e., forward stepwise strategy) is applied. …”
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Dynamical Modeling, Analysis, and Control of Information Diffusion over Social Networks: A Deep Learning-Based Recommendation Algorithm in Social Network by Kefei Cheng, Xiaoyong Guo, Xiaotong Cui, Fengchi Shan

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Adaptive Resource Optimization for LoRa-Enabled LEO Satellite IoT System in High-Dynamic Environments by Chen Zhang, Haoyou Peng, Yonghua Ji, Tao Hong, Gengxin Zhang

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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer by Chiara Frascarelli, Konstantinos Venetis, Antonio Marra, Eltjona Mane, Mariia Ivanova, Giulia Cursano, Francesca Maria Porta, Alberto Concardi, Arnaud Gerard Michel Ceol, Annarosa Farina, Carmen Criscitiello, Giuseppe Curigliano, Elena Guerini-Rocco, Nicola Fusco

“…Traditional ancillary methods like immunohistochemistry (IHC) to assess TP53 functionality face pre- and post-analytical challenges. This proof-of-concept study employed a deep learning (DL) algorithm to predict TP53 mutational status from H&E-stained whole slide images (WSIs) of BC tissue. …”
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FLIP: A Novel Feedback Learning-Based Intelligent Plugin Towards Accuracy Enhancement of Chinese OCR by Xinyue Tao, Yueyue Han, Yakai Jin, Yunzhi Wu

“…This study develops FLIP (Feedback Learning-based Intelligent Plugin), a lightweight post-processing plugin designed to improve Chinese OCR accuracy across different systems without external dependencies. …”
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Exploration design for Q-learning-based adaptive linear quadratic optimal regulators under stochastic disturbances by Vina Putri Virgiani, Shiro Masuda

“…Q-learning optimizes the state-action policy by estimating the Q-function iteratively. …”
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Optimization of PV parameters under varied environmental conditions: A hybrid secant–Newton-Raphson method by Brahim El Fahmi, Driss Saadaoui, Imade Choulli, Khalid Assalaou, Ismail Abazine, Mustapha Elyaqouti, El hanafi Arjdal, Mohammed Agdam, Yassine El aidi Idrissi

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Comparative Study on Hyperparameter Tuning for Predicting Concrete Compressive Strength by Jeonghyun Kim, Donwoo Lee

“…This study assesses the impact of hyperparameter optimization algorithms on the performance of machine learning-based concrete compressive strength prediction models. …”
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Model Predictive Control of Nonlinear System Based on GA-RBP Neural Network and Improved Gradient Descent Method by Youming Wang, Didi Qing

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Improving Event Data in Football Matches: A Case Study Model for Synchronizing Passing Events with Positional Data by Alberto Cortez, Bruno Gonçalves, João Brito, Hugo Folgado

“…Three datasets were used to perform this study: a dataset created by applying a custom algorithm that synchronizes positional and event data, referred to as the optimized synchronization dataset (OSD); a simple temporal alignment between positional and event data, referred to as the raw synchronization dataset (RSD); and a manual notational data (MND) from the match video footage, considered the ground truth observations. …”
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Soybean Yield Estimation Using Improved Deep Learning Models With Integrated Multisource and Multitemporal Remote Sensing Data by Jian Li, Junrui Kang, Ji Qi, Jian Lu, Hongkun Fu, Baoqi Liu, Xinglei Lin, Jiawei Zhao, Hengxu Guan, Jing Chang, Zhihan Liu

“…This framework synergistically integrates an optimized bidirectional hierarchical gated recurrent unit (BiHGRU), a Transformer encoder, and a novel Greenness and Water Content Composite Index, with critical parameters optimized by particle swarm optimization (PSO). …”
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Prediction of UHPC mechanical properties using optimized hybrid machine learning model with robust sensitivity and uncertainty analysis by ZhiGuang Zhou, Jagaran Chakma, Md Ahatasamul Hoque, Vaskar Chakma, Asif Ahmed

“…Each dataset was standardized and split into training (80%) and testing (20%) subsets. Hyperparameter optimization was conducted using a random search algorithm to improve prediction accuracy. …”
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The effect of using the algorithm of restrictive intraoperative fluid therapy, early immune enteral nutrition, and early patient mobilization on orthotopic liver transplantation ou... by A. M. Dzyadz'ko, M. L. Katin, O. A. Chugunova, A. F. Minov, E. G. Oganova, E. O. Santotskiy, A. E. Shcherba, O. O. Rummo, I. I. Kanus

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Application of Improved LSTM Model in Runoff Simulation in Arid Region of Northwest China: A Case Study of the Zuli River by SONG Haiping, TANG Yiran, DANG Wentao, WANG Yibo

“…The results indicate that: ① The improved LSTM model demonstrates superior performance in simulating the Zuli River, validating the adaptability of the improved strategies for complex hydrological processes. ② The GWO algorithm significantly enhances the model's prediction accuracy in the basin, confirming the effectiveness of optimization algorithms in parameter calibration. ③The GWO-LSTM-Attention model requires further validation and optimization for future daily-scale simulations and monthly runoff reconstruction.…”
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