A Survey on the Key Technologies of UAV Motion Planning by Yuquan Zhou, Li Yan, Yaxi Han, Hong Xie, Yinghao Zhao

“…However, achieving full autonomy remains a challenge as human intervention is still required in most scenarios. Motion planning, a cornerstone of UAV autonomous navigation, has garnered extensive attention, with numerous advanced algorithms having been proposed in recent years. …”
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Research on Abstraction-Based Search Space Partitioning and Solving Satisfiability Problems by Yuexin Huang, Qinzhou Niu, Yanfang Song

“…Solving satisfiability problems is central to many areas of computer science, including artificial intelligence and optimization. Efficiently solving satisfiability problems requires exploring vast search spaces, where search space partitioning plays a key role in improving solving efficiency. …”
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Advances in Pinhole and Multi-Pinhole Collimators For Single Photon Emission Computed Tomography Imaging by Jalil Islamian, AhmadReza Azazrm, Babak Mahmoudian, Esmail Gharapapagh

“…On the other hand, recent developments in collimator optimization have heightened the need for appropriate reconstruction algorithms for pinhole SPECT imaging. …”
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Machine Learning-Based Lithium Battery State of Health Prediction Research by Kun Li, Xinling Chen

“…To address the problem of predicting the state of health (SOH) of lithium-ion batteries, this study develops three models optimized using the particle swarm optimization (PSO) algorithm, including the long short-term memory (LSTM) network, convolutional neural network (CNN), and support vector regression (SVR), for accurate SOH estimation. …”
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Robust Adaptive Fractional-Order PID Controller Design for High-Power DC-DC Dual Active Bridge Converter Enhanced Using Multi-Agent Deep Deterministic Policy Gradient Algorithm for... by Seyyed Morteza Ghamari, Daryoush Habibi, Asma Aziz

“…To overcome this issue, Grey Wolf Optimization (GWO) algorithm is proposed to identify the most suitable initial gains for each agent, providing faster adaptation and consistent performance during the training process. …”
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Comparative analysis and selection of the geometry of the microphone array based on MEMS microphones for sound localisation by Andrii Riabko, Tetiana Vakaliuk, Oksana Zaika, Roman Kukharchuk, Yuriy Smorzhevsky

“…The goal is to determine the most effective array architecture and beamforming algorithms to achieve compactness, accuracy, and balanced omnidirectional coverage. …”
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A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in M... by Abhijeet Das

“…Our research in Mahanadi River Basin, Odisha, presents an enhanced methodology based on data, specifically designed to be beneficial for Water Quality (WQ) based on Synthetic Pollution Index (SPI) and machine learning models such as Long Short-Term Memory (LSTM) and Sparrow Search Algorithm (SSA), for its analysis and interpretation of extensive, intricate data sets on water quality, as well as the allocation of pollution sources or contributing elements, in order to improve knowledge of the water quality and the planning of monitoring networks for efficient water resource management. …”
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Machine learning-enhanced near-infrared spectroscopy for high-throughput phenotyping of sweetpotato sugars across raw and cooked states by Chaochen Tang, Xueying Mo, Zhimin Ma, Zhangying Wang

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Predictive Ecological Cooperative Control of Electric Vehicles Platoon on Hilly Roads by Bingbing Li, Weichao Zhuang, Boli Chen, Hao Zhang, Sheng Yu, Jianrun Zhang, Guodong Yin

“…In this paper, a novel strategy based on a decentralized model predictive control (MPC) framework, called predictive ecological cooperative control (PECC), is proposed for vehicle platoon control on hilly roads, aiming to maximize the overall energy efficiency of the platoon. Unlike most existing literature that focuses on suboptimal coordination under predefined leading vehicle trajectories, this strategy employs an approach based on the combination of a long short-term memory network (LSTM) and genetic algorithm (GA) optimization (GA-LSTM) to predict the future speed of the leading vehicle. …”
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Machine Learning Approach and Model for Predicting Proton Stopping Power Ratio and Other Parameters Using Computed Tomography Images by Charles Ekene Chika

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MINIMIZATION OF RISK OF THE ERRONEOUS DECISION IN THE ASSESSMENT OF THE IMPORTANCE OF STATISTICAL RELATIONS OF TECHNICAL AND ECONOMIC INDICATORS OF THE OBJECTS OF ELECTRIC POWER SY... by E. M. Farhadzadeh, A. Z. Muradaliyev, Yu. Z. Farzaliyev, T. K. Rafiyeva, S. A. Abdullayeva

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High-resolution image inpainting using a probabilistic framework for diverse images with large arbitrary masks by G. Sumathi, M. Uma Devi

“…The priors are constructed using cosine similarity, mean, and intensity, where intensity is computed using the improved Papoulis–Gerchberg algorithm. The image is reconstructed using the probabilistic maximum a posteriori estimate. …”
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Beyond the Current Curve: A Novel Curve Warning System Considering Subsequent Curve Speed Limits by N. S. Manikandan, Ganesan Kaliyaperumal

“…Our proposed method, incorporating adjacent curve information, demonstrates significant safety improvements, particularly in reducing the RMSE error when navigating the curves on simulated autonomous vehicles.…”
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A calibration procedure for simulation models of rural residential buildings using monthly energy bills: A case study in Zhejiang, China by Yuanyuan Wei, Song He, Ping Huang, Yuechen Duan, Bart Julien Dewancker, Luyao Zhou

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Time-Variation Damping Dynamic Modeling and Updating for Cantilever Beams with Double Clearance Based on Experimental Identification by Yunhe Zhang, Fanjun Meng, Xueguang Li, Wei Song, Dashun Zhang, Faping Zhang

“…The quantum genetic algorithm (QGA) is used to optimize the scale factor, which determines the identification accuracy and calculation efficiency. …”
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YOLOv5-DTW: Gesture recognition based on YOLOv5 and dynamic time warping for digital media design by Lu Zhao, Jing Yu

“…In the recognition stage, firstly, the background and sensor thermal noise are used to enhance the classification data set, and the background optimization preprocessing algorithm is designed to improve the adaptability of the model to the complex background. …”
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Multi-Condition Rolling Bearing Fault Denoising Method and Application Based on RIME-VMD by Xin Zhao, Xuebin Liu, Hanshan Li

“…The experimental results show that the RIME-VMD method can effectively remove most of the noise in the rolling bearing fault signal, and the performance evaluation indexes of this method are better than other existing optimization algorithms. …”
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An Enhanced Generative Adversarial Network Prediction Model Based on LSTM and Attention for Corrosion Rate in Pipelines by Pujun Long, Mi Liang, Hongjian Chen, Qin Yang

“…This model integrates an improved Generative Adversarial Network with Grey Wolf Optimization and Support Vector Regression (LAGAN-GWO-SVR). …”
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Evolutionary fuzzy learning for Chinese medicine liver syndrome differentiation by Jia-Yu Yan, Peng-Wei Zhang, Wei-Guo Sheng, Jun-Ping Shi, Wei Ni, Li Li, Yu-Jun Zheng

“…To determine the most appropriate fuzzy membership functions of the fuzzy learning machines, an evolutionary algorithm was employed to optimize the types and parameters of the fuzzy functions simultaneously. …”
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Analysis of Weak Links in the Mechanized Mining of Underground Metal Mines: Insights from Machine Learning and SHAP Explainability Models by Chengye Yang, Keping Zhou, Jielin Li

“…These findings offer valuable insights and a robust foundation for optimizing design and improving production management in mechanized mining operations.…”
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