Fine-Tuning Quadcopter Control Parameters via Deep Actor-Critic Learning Framework: An Exploration of Nonlinear Stability Analysis and Intelligent Gain Tuning by Hassan Moin, Umer Hameed Shah, Muhammad Jawad Khan, Hasan Sajid

“…This study implements an optimal gain self-tuning framework for the altitude, attitude, and position controllers of a 6 degrees-of-freedom nonlinear drone system using a deep reinforcement learning algorithm with continuous observation and action spaces. …”
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Numerical Solution of the Inverse Thermoacoustics Problem Using QFT and Gradient Method by Syrym E. Kasenov, Aigerim M. Tleulesova, Almas N. Temirbekov, Zholaman M. Bektemessov, Rysbike A. Asanova

“…The inverse problem was reduced to an optimization problem, where the objective function was minimized using gradient methods, including the accelerated Nesterov algorithm. …”
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AI-enhanced fire detection and suppression system for autonomous ships by Hyuk Lee, Jung Hoon Chung, Hyun Chung, Jong-Hwan Kim, Yongho Yoo, Gil Hyuk Lim, Won-Sun Ruy

“…In this paper, we introduce an innovative AFDSS that integrates RGB, infrared (IR), and ultraviolet (UV) sensors to reduce false alarms and employ a reinforcement learning algorithm to optimize water spray under sea conditions. …”
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State of Health Estimation for Lithium-Ion Batteries Using Electrochemical Impedance Spectroscopy and a Multi-Scale Kernel Extreme Learning Machine by Jichang Peng, Ya Gao, Lei Cai, Ming Zhang, Chenghao Sun, Haitao Liu

“…A multi-scale kernel extreme learning machine (MS-KELM), optimized by the Sparrow Search Algorithm (SSA), estimates battery SOH with an average mean absolute error (MAE) of 1.37% and a root mean square error (RMSE) of 1.76%. …”
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Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…While VQ is a technique that reduces model size by grouping similar parameters, incremental clustering, implemented via the AutoCloud K-Fixed algorithm, preserves accuracy during compression. …”
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Investigation of Load Sharing and Dynamic Load Characteristics of a Split Torque Transmission System with Double-Helical Gear Modification by Xuan Liu, Zongde Fang, Haitao Jia, Ning Zhao, Yunbo Shen, Hui Guo, Xijin Zhang

“…The modified tooth surface of a third-stage double-helical gear is obtained by optimizing the amplitude of static loaded transmission error and meshing-in impact via nondominated sorting genetic algorithm-II (NSGA-II). …”
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Phase Error Correction in Sparse Linear MIMO Radar Based on the Equivalent Phase Center Principle by Wenyuan Shao, Jianmin Hu, Yicai Ji, Jun Pan, Guangyou Fang

“…Multiple-input multiple-output (MIMO) technology is widely used in the field of radar imaging. Array sparse optimization reduces the hardware cost of MIMO radar, while virtual aperture and the equivalent phase center (EPC) principle simplify the radar signal model and reduce the computation and complexity of imaging algorithms. …”
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Development of Automatic Balancing Application forFashion Company Using Artificial Intelligence by May Alrasheed, Mohamed Jmali, Thouraya Hamdi

“…It focuses on utilising ant colony algorithms for optimal balancing. The results show the significance of these algorithms in attaining optimal balancing in production systems. …”
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Bamboo bio composite: A renewable and sustainable sound absorber for acoustic comfort in indoor settings by Hassan Irvani, Hassan Asilian Mahabadi, Ali Khavanin, Ali Safari Variani, Mohammad Javad SheikhMozafari

“…Porosity and airflow resistivity (AFR) parameters were directly determined, while the parameters of tortuosity, viscous, and thermal characteristic length were inversely determined using the differential evolution algorithm in MATLAB. …”
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SafeTrack: Secure Tracking Protocol for Mobile Sensor Nodes in Unstable Wireless Sensor Networks by Ali Adnan Al-Khazraji, Fatimah Abdulridha Rashid

“…It also incorporates an Adaptive Routing Algorithm (ARA) and an Energy Optimization Module (EOM) to enable both efficient resource utilization and resilience to changes in dynamic network conditions. …”
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Research on intelligent energy management strategies for connected range-extended electric vehicles based on multi-source information by Xuewen Zhai, Hanwu Liu, Wencai Sun, Zihang Su

“…Abstract Reliance solely on vehicle-specific information, while neglecting multi-source information such as traffic flow and traffic light status, results in difficulties in optimizing energy allocation based on complex road conditions. …”
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Modeling and control of automatic voltage regulation for a hydropower plant using advanced model predictive control by Ebunle Akupan Rene, Willy Stephen Tounsi Fokui

“…The findings were compared with those derived from an optimal proportional integral derivative (PID) controller designed using the artificial bee colony (ABC) algorithm. …”
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Machine learning approach for prediction of safe mud window based on geochemical drilling log data by Hongchen Cai, Yunliang Yu, Yingchun Liu, Xiangwei Gao

“…Traditional geomechanical methods for SMW determination face challenges in handling complex, nonlinear relationships within drilling datasets.PurposeThis study aims to develop robust machine learning (ML) models to predict two key SMW parameters—Mud Pressure below shear failure (MWsf) and tensile failure (MWtf)—using geochemical drilling log data from Middle Eastern carbonate reservoirs.MethodsHybrid ML models combining Least Squares Support Vector Machine (LSSVM) and Multilayer Perceptron (MLP) with optimization algorithms (Gray Wolf Optimization, GWO; Grasshopper Optimization Algorithm, GOA) were trained on 2,820 data points from three wells. …”
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Dynamic Adaptation for Independent Task Scheduling Using Dynamic Programming in Multiprocessor Systems by Lotfi BENDIAF, Ahmed HARBOUCHE, Mohammed Amin TAHRAOUI

“…DyTAg leverages dynamic programming to minimize makespan while maximizing resource utilization, ensuring that tasks are allocated optimally even in complex, heterogeneous environments. …”
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Land Use Transition and Regional Development Patterns Under Shared Socioeconomic Pathways: Evidence from Prefecture-Level Cities in China by Xiaodong Zhang, Mingjie Yang, Rui Guo, Yaolong Li, Fanglei Zhong

“…This study integrates the population–development–environment model with back propagation (BP) neural networks, a supervised learning algorithm, to analyze how differentiated development trajectories reshape land systems. …”
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Impact of rainy season on approach trajectories in high-altitude airport terminal maneuvering area: a clustering analysis by Jianxiong Chen, Jingtao Wang, Fan Li, Lin Zou

“…After data preprocessing, a clustering algorithm was used to identify trajectory patterns and detect outlier trajectories. …”
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Performance Analysis of Three-Phase Interleaved Buck-Boost Converter in Wind Energy Maximum Power Point Tracking by Muhammad Qasim Nawaz Sciences, Wei Jiang Sciences, Aimal Khan Sciences

“… This paper presents a performance analysis of a three-phase interleaved buck-boost converter integrated with a Maximum Power Point Tracking (MPPT) algorithm using the Perturb and Observe (P&O) method for an independent wind energy generation system. …”
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Game-based resource allocation in heterogeneous downlink CR-NOMA network without subchannel sharing by Deepa Das, Rajendra Kumar Khadanga, Deepak Kumar Rout, Md. Minarul Islam, Taha Selim Ustun

“…We frame this joint optimization of SU cluster formation and power allocation as a cooperative multi-armed bandit game. …”
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Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples by Weiheng KONG, Lingwei ZENG, Yu RAO, Sha CHEN, Xu WANG, Yanting YANG, Yixiang DUAN, Qingwen FAN

“…Different element quantitative models were constructed for each rock type. The kNN algorithm was selected using cross-validation to determine the optimal k value, and the key punishment parameter C and RBF width parameter γ of the SVM algorithm were determined using a grid search method. …”
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DQN-Based Shaped Reward Function Mold for UAV Emergency Communication by Chenhao Ye, Wei Zhu, Shiluo Guo, Jinyin Bai

“…The experimental outcomes underscore the prowess of our methodology in effectively curtailing training time while augmenting convergence rates. In summary, our work underscores the potential of leveraging sophisticated virtual environments and refined reinforcement learning techniques to optimize UAVs deployment in emergency communication contexts.…”
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