Design of Instrumentation and Control Components of Power Distribution Systems by Y. A. Klimenko, Y. E. Lvovich, A. P. Preobrazhensky

“…In recent years, the development of high-voltage power systems has received a boost due to the need for infrastructural support for priority development areas. Universal models and algorithms are required to implement processes in power components and identify their optimal parameters. …”
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Enhanced Automatic Generation Control in Multiarea Power Systems: Crow Search Optimized Cascade FOPI‐TIDDN Controller With Integrated Renewable Solar Thermal Models and HVDC Lines... by Naladi Ram Babu, Pamarthi Sunitha, Ganesh Pardhu B. S. S., Sanjeev Kumar Bhagat, Adireddy Ramesh, Arindita Saha, Wulfran Fendzi Mbasso, Pradeep Jangir, Ahmed Hossam‐Eldin

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Optimization Procedures in Affine Model Checking by N. O. Garanina

“…In this paper we suggest improved algorithms for an algebraic data representation, namely, optimization algorithms for affine data structures.…”
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YOLOv8-E: An Improved YOLOv8 Algorithm for Eggplant Disease Detection by Yuxi Huang, Hong Zhao, Jie Wang

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Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification by Shahad S. Alkamli, Hala M. Alshamlan

“…This study explores the performance of hybrid bio-inspired algorithms and deep learning techniques for gene selection and cancer classification. …”
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DQN Simulation Model of Green Cooperative Market Behavior of Multi-Load Users for Optimal Evolution of New-Type Power System by ZHANG Shuo, YUAN Chunhui, LI Yingzi, XIAO Yangming, WEI Ming, HE Yunzheng

“…[Methods] First， the green cooperative market behavior and bidding behavior of multiple loads were analyzed and a multiple-load market bidding decision model was constructed. Second， the decision-making process of multiple loads and the entire transaction simulation process of the power market were constructed， and the deep reinforcement learning DQN algorithm was applied to analyze the behavior of multiple loads participating in market transactions and obtain their optimal bidding strategies. …”
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Integration of improved APF and RRT algorithms for enhanced path planning in mobile robotics by Yu Liangwu, Han Jianggui, Ma Boweng, Liu Bao, He Zhiying

“…Firstly, the mathematical model of the traditional APF algorithm was improved to solve the problems of unbalanced force and unreachable targets. …”
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Tracking Control of CSTRs Based on Improved OU Noise and the TD3 Algorithm by Hongyan Shi, Xiaofei Wu, Guogang Wang

“…To enhance exploration capabilities and convergence speed, fractional-order characteristics and a reward feedback mechanism are introduced into the OU noise, dynamically adjusting noise intensity to improve adaptability to complex states and optimize the exploration strategy of the TD3 algorithm. …”
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Small object detection algorithm based on improved YOLOv10 for traffic sign by Yukang Zou, Scarlett Liu

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A Lightweight Detection Method for Meretrix Based on an Improved YOLOv8 Algorithm by Zhongxu Tian, Sifan Hou, Xiaoxue Yue, Xuewen Hu

“…Clam farms are typically located in remote areas with limited computational resources, making it challenging to deploy traditional deep learning-based object detection methods due to their large model size and high computational demands. To address this issue, this paper proposes a lightweight detection method, YOLOv8-RFD, based on an improved YOLOv8 algorithm, tailored for clam sorting applications. …”
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Improved Crosstalk Reduction on Multiview 3D Display by Using BILS Algorithm by Xiaoyan Wang, Chunping Hou

“…Furthermore, an improved crosstalk reduction method is proposed to alleviate crosstalk by searching for the optimal integral intensity values of subpixels on the synthetic image. …”
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Comprehensive Comparison and Validation of Forest Disturbance Monitoring Algorithms Based on Landsat Time Series in China by Yunjian Liang, Rong Shang, Jing M. Chen, Xudong Lin, Peng Li, Ziyi Yang, Lingyun Fan, Shengwei Xu, Yingzheng Lin, Yao Chen

“…When considering different forest disturbance types, COLD achieved the highest accuracies for Fire, Harvest, and Other disturbances, while CCDC was most accurate for Forestation. These findings highlight the necessity of region-specific calibration and parameter optimization tailored to specific disturbance types to improve forest disturbance monitoring accuracy, and also provide a solid foundation for future studies on algorithm modifications and ensembles.…”
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A novel method for distracted driving behaviors recognition with hybrid CNN-BiLSTM-AM model by Dengfeng Zhao, Haojie Li, Zhijun Fu, Bao Ma, Fang Zhou, Chaohui Liu, Wenbin He

“…A fully connected neural network layer is applied to establish a nonlinear mapping relationship between the extracted features and driving behavior categories. Bayesian optimization algorithm is adopted to automatically optimize hyperparameters of the network so as to improve training efficiency and performance of the proposed model. …”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…The investigation confirms that Optuna-optimized models are at least 13 % more precise than GA and PSO models. …”
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An Optimization Method for Multi-Robot Automatic Welding Control Based on Particle Swarm Genetic Algorithm by Lu Chen, Jie Tan, Tianci Wu, Zengxin Tan, Guobo Yuan, Yuhao Yang, Chiang Liu, Haoyu Zhou, Weisi Xie, Yue Xiu, Gun Li

“…The method first constructs a multi-axis robotic kinematic model to provide constraint conditions. Then, the PSO (particle swarm optimization) algorithm, which integrates penalty functions into the fitness evaluation, is used to determine the optimal welding path by simulating collective behavior within a group. …”
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An Improved YOLOv7-Tiny-Based Algorithm for Wafer Surface Defect Detection by Mengyun Li, Xueying Wang, Hongtao Zhang, Xiaofeng Hu

“…Experiments conducted on a self-constructed dataset show that the improved algorithm achieved a mean Average Precision (mAP) of 90.1%, representing a 3.2% increase over the original algorithm. …”
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Improved salp swarm algorithm-driven deep CNN for brain tumor analysis by Umang Kumar Agrawal, Nibedan Panda, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…Consequently, optimal candidate solutions with improved and faster convergence toward global optima are achieved.…”
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Enhancing Wind Power Forecasting Accuracy Based on OPESC-Optimized CNN-BiLSTM-SA Model by Lele Wang, Dongqing Zhang

“…This study proposes OPESC-CNN-BiLSTM-SA, a hybrid model combining an optimized escape algorithm (OPESC), convolutional neural network (CNN), bidirectional long short-term memory (BiLSTM) network, and self-attention (SA). …”
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Small Ship Detection Based on Improved Neural Network Algorithm and SAR Images by Jiaqi Li, Hongyuan Huo, Li Guo, De Zhang, Wei Feng, Yi Lian, Long He

“…Therefore, based on the YOLOv5s model, this paper improves its backbone network and feature fusion network algorithm to improve the accuracy of ship detection target recognition. …”
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Energy-Optimized Path Planning and Tracking Control Method for AUV Based on SOC State Estimation by Guangyi Yang, Zhenning Xu, Feng Wang, Xiaoyu Zhang

“…This paper proposes a path planning and trajectory tracking control framework for autonomous underwater vehicles (AUVs) combined with battery state of charge (SOC) optimization. The framework incorporates the Grasshopper Optimization Algorithm (GOA) with the Artificial Potential Field Algorithm (APF) to achieve global path planning and local path optimization while minimizing energy consumption as an objective. …”
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