Lantern-Explorer: A Collision-Avoidance Autonomous Exploration Drone System Based on Laser SLAM with Optimized Hardware and Software by L. Zhu, L. Zhu, R. Zhong, R. Zhong, D. Xie, D. Xie, X. Yuan, X. Yuan

“…This algorithm, based on the LiDAR FOV model, optimizes the strategy for detecting unknown frontiers, improving the efficiency of boundary extraction and viewpoint generation. …”
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A hybrid optimization-enhanced 1D-ResCNN framework for epileptic spike detection in scalp EEG signals by Priyaranjan Kumar, Prabhat Kumar Upadhyay

“…Abstract In order to detect epileptic spikes, this paper suggests a deep learning architecture that blends 1D residual convolutional neural networks (1D-ResCNN) with a hybrid optimization strategy. The Layer-wise Adaptive Moments (LAMB) and AdamW algorithms have been used in the model’s optimization to improve efficiency and accelerate convergence while extracting features from time and frequency domain EEG data. …”
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Dung beetle optimizer based on mean fitness distance balance and multi-strategy fusion for solving practical engineering problems by Wanru Tang, Haoze Qin, Shuang Kang

“…Abstract As a swarm intelligence algorithm, Dung beetle optimizer (DBO) was inspired by the behavior pattern of dung beetles for survival. …”
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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

“…Firstly, analytical models are formulated to evaluate the SEE and secrecy sum rate (SSR) of the secondary network in NOMA-UCRN, considering residual hardware impairments, imperfect successive interference cancellation conditions, and interference power constraints at the primary receiver. Subsequently, joint optimal transmit power allocation (JOTPA) is ascertained for the secondary users (SUs) at the secondary transmitter and the secondary relay, with the aim of maximizing the SEE while satisfying constraints on tolerable interference power at the primary receiver and minimum data rates for the SUs. …”
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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

“…The experimental results demonstrate that SGDO-SLAM reduces the absolute trajectory error performance metrics by 95% compared to the ORB-SLAM2 algorithm, while maintaining real-time efficiency and achieving state-of-the-art accuracy in dynamic scenarios.…”
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Intelligent data-driven system for mold manufacturing using reinforcement learning and knowledge graph personalized optimization for customized production by Chengcai He, Jiaxing Deng, Jingchun Wu, Beicheng Qin, Jinxiang Chen, Yan Li, Qiangsheng Huang

“…Overall, the proposed system significantly improves the level of customization in mold manufacturing while enhancing production efficiency and maintaining quality standards. …”
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Enhanced Stability and Performance of Islanded DC Microgrid Systems Using Optimized Fractional Order Controller and Advanced Energy Management by Md. Wahidujjaman, Tasnim Ul Bari, Md. Shafiul Alam, Md. Rashidul Islam, Md. Alamgir Hossain, Md. Arafat Hossain, Md. Rafiqul Islam Sheikh

“…To address these issues, this study proposes the use of an optimized fractional order PI (FOPI) controller and an efficient energy management algorithm. …”
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Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…Finally, the model’s prediction accuracy is further enhanced by optimizing the hyperparameters of XGBoost through Bayesian optimization (BO) algorithms, resulting in the development of MM–BO–XGBoost models. …”
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Improving Soil Heavy Metal Lead Inversion Through Combined Band Selection Methods: A Case Study in Gejiu City, China by Ping He, Xianfeng Cheng, Xingping Wen, Yi Cao, Yu Chen

“…To construct a preliminary Pb content prediction model, the initial selection of spectral bands utilized methods including CARS (Competitive Adaptive Reweighted Sampling), GA (Genetic Algorithm), MI (mutual information), SPA (Successive Projections Algorithm), and WOA (Whale Optimization Algorithm). …”
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Efficient cooling capability in microchannel heat sink reinforced with Y-shaped fins: Based on artificial neural network, genetic algorithm, Pareto front, and numerical simulation by Xiang Ma, Ali Basem, Pradeep Kumar Singh, Rebwar Nasir Dara, Ahmad Almadhor, Amira K. Hajri, Raymond Ghandour, Barno Abdullaeva, H. Elhosiny Ali, Samah G. Babiker

“…The applied cost functions demonstrated the high accuracy of the models in predicting system performance. A genetic algorithm was employed for single-objective optimization targeting three criteria: maximizing total efficiency, minimizing pressure drop, and maximizing the Nusselt number. …”
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Integration of Hybrid Machine Learning and Multi-Objective Optimization for Enhanced Turning Parameters of EN-GJL-250 Cast Iron by Yacine Karmi, Haithem Boumediri, Omar Reffas, Yazid Chetbani, Sabbah Ataya, Rashid Khan, Mohamed Athmane Yallese, Aissa Laouissi

“…Advanced optimization models including improved grey wolf optimizer–deep neural networks (DNN-IGWOs), genetic algorithm–deep neural networks (DNN-GAs), and deep neural network–extended Kalman filters (DNN-EKF) were compared with traditional methods like Support Vector Machines (SVMs), Decision Trees (DTs), and Levenberg–Marquardt (LM). …”
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Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model by Kai Cheng, Xiaokang Zhang, Keping Zhou, Chenao Zhou, Jielin Li, Chun Yang, Yurong Guo, Ranfeng Wang

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Optimization of heat and mass transfer in chemically radiative nanofluids using Cattaneo-Christov fluxes and advanced machine learning techniques by Shazia Habib, Saleem Nasir, Zeeshan Khan, Abdallah S. Berrouk, Waseem Khan, Saeed Islam

“…This functionality empowers specialists to oversee the progression of optimization, identify convergence patterns, and adjust algorithms to achieve superior results, thereby making a remarkable contribution to heat transfer and fluid dynamics.…”
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Designing Predictive Analytics Frameworks for Supply Chain Quality Management: A Machine Learning Approach to Defect Rate Optimization by Zainab Nadhim Jawad, Balázs Villányi

“…The framework employs advanced ML algorithms, including extreme gradient boosting (XGBoost), support vector machines (SVMs), and random forests (RFs), to accurately predict defect rates and derive actionable insights for supply chain optimization. …”
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Mathematical Modeling of Optimal Drone Flight Trajectories for Enhanced Object Detection in Video Streams Using Kolmogorov–Arnold Networks by Aida Issembayeva, Oleksandr Kuznetsov, Anargul Shaushenova, Ardak Nurpeisova, Gabit Shuitenov, Maral Ongarbayeva

“…While most research focuses on improving detection algorithms, the relationship between flight parameters and detection performance remains poorly understood. …”
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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Further, the selection of features is performed by DBO algorithm, which removes redundant features and helps to improve efficiency and accuracy. …”
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Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study by Una Kjällquist, Nikos Tsiknakis, Balazs Acs, Sara Margolin, Luisa Edman Kessler, Scarlett Levy, Maria Ekholm, Christine Lundgren, Erik Olsson, Henrik Lindman, Antonios Valachis, Johan Hartman, Theodoros Foukakis, Alexios Matikas

“…Purpose: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused on ROR/Prosigna. …”
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Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage by Yiwen Geng, Qi Liu, Hao Zheng, Shitong Yan

“…Stage II employs an improved multi-objective particle swarm optimization (IMOPSO) algorithm to optimize HESS power allocation, minimizing unit hydrogen production cost and reducing average battery charge–discharge depth. …”
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Online Tool Wear Monitoring via Long Short-Term Memory (LSTM) Improved Particle Filtering and Gaussian Process Regression by Hui Xu, Hui Xie, Guangxian Li

“…However, traditional Gaussian Process Regression (GPR) models are constrained by linear assumptions, while conventional filtering algorithms struggle in noisy environments with low signal-to-noise ratios. …”
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Verifiable secure image retrieval for cloud-assisted IoT environments by GUO Jiaqi, MA Zhi, WANG Wensheng, TIAN Cong, DUAN Zhenhua

“…The proposed scheme improves image retrieval accuracy and security while optimizing computational and storage resources, making it suitable for cloud-assisted IoT environments.…”
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