Research on improving the ranging accuracy of ships with stereo vision through Kalman filter optimization. by Zhongbo Peng, Jie Han, Liang Tong, Lumeng Wang, Dan Liu, Shijie Sun

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A Review of Smart Grid Evolution and Reinforcement Learning: Applications, Challenges and Future Directions by Na Xu, Zhuo Tang, Chenyi Si, Jinshan Bian, Chaoxu Mu

“…This study compares the applicability, advantages, and limitations of different reinforcement learning algorithms in practical scenarios, and reveals core challenges such as state space complexity, learning stability, and computational efficiency. …”
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Energy-efficient data collection optimization for dual-UAV-assisted relay marine networks by Fukang Deng, Haibo Luo, Furong Xu, Ming Li, Jianshan Zhang

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Optimal fusion β-quaternion filtering from delayed observations and packet losses with compensation strategy under properness by J. D. Jiménez-López, R. M. Fernández-Alcalá, F. Gutiérrez-Trujillo, E. Grassucci, D. Comminiello

“…Under first-order properness conditions, a recursive algorithm is developed to compute the optimal filter. …”
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Intelligent Interior Design Systems: Optimizing Layouts and Aesthetics Using AI and User Data by Zhe Ji, Yan Yu

“…Optimization algorithms, including hybrid evolutionary strategies, are guided by learned aesthetic and functionality scores to efficiently explore the solution space. …”
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Hybrid Ensemble Pruning Using Coevolution Binary Glowworm Swarm Optimization and Reduce-Error by Xuhui Zhu, Zhiwei Ni, Pingfan Xia, Liping Ni

“…Therefore, a compromise between them can ensure that the ELMs remain good diversity and high precision, but finding the compromise brings a heavy computational burden. It is hard to look for the exact result via the searching of intelligent algorithms or pruning of diversity measures. …”
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A novel framework for optimizing residential load response planning with consideration of user satisfaction by Mohammad Hossein Erfani Majd, Gholam-Reza Kamyab, Saeed Balochian

“…The proposed method utilizes the Meerkat Optimization Algorithm (MOA), which is compared against other optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Teaching-Learning-Based Optimization (TLBO). …”
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Federated learning secrecy rate optimization for 6G intelligent reflecting surface assistance by WU Yingying, MAO Bomin

“…Finally, the deep deterministic policy gradient (DDPG) algorithm was employed to solve the optimization problem, with the action space defined as the transmit power and IRS phase shift matrix, and the channel state information and previous action constituting the state space. …”
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INFORMATION TECHNOLOGIES IN OPTIMIZING SCIENTIFIC RESEARCH IN THE SPHERE OF THEORETICAL AND APPLIED LINGUISTICS IN THE DIGITAL AGE by M. V. Kamensky

“…Recommendations are given for the best practices of integrating the corpus management, lexicographic, machine and computer-aided translation, and phonetic software, as well as programming languages with support for natural language processing algorithms, into the linguistic scientific workflow. …”
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An accuracy-privacy optimization framework considering user’s privacy requirements for data stream mining by Waruni Hewage, R. Sinha, M. Asif Naeem

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Robotic Arm Trajectory Planning in Dynamic Environments Based on Self-Optimizing Replay Mechanism by Pengyao Xu, Chong Di, Jiandong Lv, Peng Zhao, Chao Chen, Ruotong Wang

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Efficient Conical Area Differential Evolution with Biased Decomposition and Dual Populations for Constrained Optimization by Weiqin Ying, Bin Wu, Yu Wu, Yali Deng, Hainan Huang, Zhenyu Wang

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Multi-Objective Ant Colony Optimization (MOACO) Approach for Multi-Document Text Summarization by Murali Krishna Muddada, Jayavani Vankara, Sekharamahanti S. Nandini, Girija Rani Karetla, Kaparapu Sowjanya Naidu

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Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization by Serdar Ekinci, Davut Izci, Veysel Gider, Laith Abualigah, Mohit Bajaj, Ievgen Zaitsev

“…A new approach is proposed which combines the quadratic interpolation optimization (QIO) algorithm with the RPIDD2 controller, taking advantage of the fast convergence, low computational cost and high accuracy of QIO. …”
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Advancements in Optimization Techniques for Active Magnetic Bearing Systems: Current Trends and Future Directions by Tasnemul Hasan Nehal, Waleed M. Hamanah, Mohammad Ali Abido

“…This review delves into cutting-edge optimization techniques for AMBs, from time-tested methods like PID control to innovative approaches such as metaheuristic algorithms, multi-objective optimization, and AI-powered strategies including reinforcement learning and iterative learning control. …”
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Optimizing electric vehicle energy consumption prediction through machine learning and ensemble approaches by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adeeb Noor, Sufyan Ali Memon

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Optimization of university dormitory renovation in severe cold regions under the impact of climate change by Anqi Wang, Shuhua Yu, Chunhui Shi, Yanhua An

“…The hierarchical optimization strategy allows NSGA-Ⅱ to optimize building performance with relatively low computational resources when dealing with high-dimensional objectives. …”
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YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

“…To overcome these limitations, this paper introduces YOLOv11-GSF, a real-time strawberry ripeness detection algorithm based on YOLOv11, which incorporates several innovative features: a Ghost Convolution (GhostConv) convolution method for generating rich feature maps through lightweight linear transformations, thereby reducing computational overhead and enhancing resource utilization; a C3K2-SG module that combines self-moving point convolution (SMPConv) and convolutional gated linear units (CGLU) to better capture the local features of strawberry ripeness; and a F-PIoUv2 loss function inspired by Focaler IoU and PIoUv2, utilizing adaptive penalty factors and interval mapping to expedite model convergence and optimize ripeness classification. …”
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A Probabilistic Approach to Surrogate‐Assisted Multi‐Objective Optimization of Complex Groundwater Problems by Reygie Q. Macasieb, Jeremy T. White, Damiano Pasetto, Adam J. Siade

“…Therefore effective management of groundwater resources often involves some form of multi‐objective optimization (MOO). Many existing software tools offer simulation model‐enabled optimization, including evolutionary algorithms, for solving MOO problems. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…We evaluated three optimization approaches—Grid Search (GS), Random Search (RS), and Bayesian Search (BS)—across three machine learning algorithms—Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). …”
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