A Study on Canopy Volume Measurement Model for Fruit Tree Application Based on LiDAR Point Cloud by Na Guo, Ning Xu, Jianming Kang, Guohai Zhang, Qingshan Meng, Mengmeng Niu, Wenxuan Wu, Xingguo Zhang

“…In the domain of point cloud feature extraction, an improved Alpha Shape algorithm is proposed for extracting point cloud contours. …”
Get full text

Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment by Jianzhao Sun

Get full text

A Novel Time Delay Nonsingular Fast Terminal Sliding Mode Control for Robot Manipulators with Input Saturation by Thanh Nguyen Truong, Anh Tuan Vo, Hee-Jun Kang

“…Manipulator systems are increasingly deployed across various industries to perform complex, repetitive, and hazardous tasks, necessitating high-precision control for optimal performance. However, the design of effective control algorithms is challenged by nonlinearities, uncertain dynamics, disturbances, and varying real-world conditions. …”
Get full text

RBCKF-Based Vehicle State Estimation by Adaptive Weighted Fusion Strategy Considering Composite-State Tire Model by Xi Chen, Xinlong Cheng

“…Meanwhile, considering the adaptive and dynamic adjustment capabilities of the observation system in complex state-change scenarios, an estimation strategy based on adaptive weight fusion and a model-based estimator is proposed. The results confirm that the robust bias compensation Kalman filter can ensure estimation exactitude and robustness when the vehicle state fluctuates greatly, and the proposed fusion strategy can ensure that the vehicle maintains optimal estimation performance during operating condition switching.…”
Get full text

Fast fault diagnosis of smart grid equipment based on deep neural network model based on knowledge graph. by Lin Jun, Zhou Chenliang

“…It can not only meet the demand of users and realize the optimal allocation of resources, but also improve the safety, economy and reliability of power supply, it has become a major trend in the future development of electric power industry. …”
Get full text

Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations by Sumit Singh Dhanda, Deepak Panwar, Chia-Chen Lin, Tarun Kumar Sharma, Deependra Rastogi, Shantanu Bindewari, Anand Singh, Yung-Hui Li, Neha Agarwal, Saurabh Agarwal

“…In genomics, ML methods enabled nuanced disease subtype discovery and improved the accuracy of cancer risk assessment and pharmacogenomic modeling. …”
Get full text

A deep learning-based hybrid method for PM2.5 prediction in central and western China by Zuhan Liu, Zihai Fang, Yuanhao Hu

“…The model integrates the transformer and LSTM architectures and employs parameter optimization through the particle swarm optimization (PSO) algorithm. …”
Get full text

Qualitative modification of geometrically oriented methods for constructing spatial curves in C3D FairCurveModeler by V. G. Mufteev, F. T. Ziganshina, V. I. Gumerov, R. I. Nabiev, G. M. Efimova

“…The article provides a detailed algorithm for improving the C3D FairCurveModeler commands for constructing a class F spatial curve with approximation by a rational cubic spline Bezier curve (NURBzS-curve) and with approximation by a highdegree B-spline curve. …”
Get full text

Smart IoT Energy Optimisation and Localisation Monitoring for E-Bike Sharing by Mawada Mohamed, Siti Fauziah Toha, Md Ataur Rahman, Moh. Khairudin

“…However, existing systems face challenges such as limited input parameters for modeling, leading to inefficiencies in energy optimization algorithms and power assist mechanisms. …”
Get full text

Application of Machine Learning for Adaptive Trajectory Control of UAVs Under Uncertainty by Alexander S. Ermilov, Olga A. Saltykova

“…Special attention is given to the practical application of ML for environmental change prediction and flight trajectory optimization. Examples of real-world ML algorithm implementations include successful developments by Russian and foreign companies, demonstrating high levels of autonomy and adaptive control. …”
Get full text

A study on monthly sales forecasting of new energy vehicles in urban areas using the WOA-BiGRU model. by Xiangtu Li

“…The Whale Optimization Algorithm (WOA) is then employed to optimize the parameters of the Bidirectional Gated Recurrent Unit (BiGRU) model, thereby proposing a WOA-BiGRU-based model for monthly sales prediction for urban NEVs. …”
Get full text

A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping by Radhwan A. Saleh, Ahmed M. Al-Areeq, Amran A. Al Aghbari, Mustafa Ghaleb, Mohammed Benaafi, Nabil M. Al‑Areeq, Baqer M. Al-Ramadan

“…Through comprehensive comparisons with established algorithms such as the Artificial Bee Colony (ABC) and Gray Wolf Optimizer (GWO), MSA refined the selection, identifying 'elevation’ and 'distance to streams’ as optimal factors. …”
Get full text

Estimation of Flood Inundation Area Using Soil Moisture Active Passive Fractional Water Data with an LSTM Model by Rekzi D. Febrian, Wanyub Kim, Yangwon Lee, Jinsoo Kim, Minha Choi

“…Accurate flood monitoring and forecasting techniques are important and continue to be developed for improved disaster preparedness and mitigation. Flood estimation using satellite observations with deep learning algorithms is effective in detecting flood patterns and environmental relationships that may be overlooked by conventional methods. …”
Get full text

Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches by Kassem Danach, Louai Saker, Hassan Harb

“…In contrast, the VAE-based approach leverages deep learning to model historical routing patterns and autonomously generate new heuristics tailored to problem-specific characteristics. …”
Get full text

Large Language Model and Digital Twins Empowered Asynchronous Federated Learning for Secure Data Sharing in Intelligent Labeling by Xuanzhu Sheng, Chao Yu, Xiaolong Cui, Yang Zhou

“…By analysising and comparing and with other existing asynchronous federated learning algorithms, the experimental results show that our proposed method outperforms other algorithms in terms of performance, such as model accuracy and running time. …”
Get full text

Stackelberg Game Based on Trajectory Prediction for Lane Change in Mixed Traffic by Baichuan Shi, Li Zhai, Chang Liu

“…The method develops a utility function for human-driven vehicles incorporating driving styles and safety-comfort-efficiency factors, with a corresponding cost function for autonomous vehicles. An improved Stackelberg game model integrates trajectory prediction of human-driven vehicles, while a bi-level optimization algorithm combining model predictive control and genetic algorithms jointly optimizes acceleration sequences and lane-change timing. …”
Get full text

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir, Aiman Erbad, Bechir Hamdaoui, Samir Brahim Belhaouari, Mohsen Guizani, Thang X. Vu

“…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…”
Get full text

New Hybrid Method for Buffer Positioning and Production Control Using DDMRP Logic in Smart Manufacturing by Sahar Habbadi, Ismail El Mouayni, Brahim Herrou, Souhail Sekkat

“…To identify the optimal buffer locations, a Genetic Algorithm (GA) is employed. …”
Get full text

Adaptive data driven multi period power supply recovery method for distribution networks by Xi Ye, Meng Yang, Zhihong Yang, Qing Xiang, Yazhuo Li

“…Finally, simulations on the improved IEEE-33 bus system and actual example systems verify that the adaptive data driven power supply recovery model for distribution networks can reduce conservatism and improve the robustness of the optimization results. …”
Get full text

Adaptive Feedforward Vibration Control of Helicopter Cabin Floor Driven by Piezoelectric Stack Actuators: Modeling, Simulation and Experiments by Laishou Song, Yingquan Wang, Xiaoyu Shen

“…A scale helicopter airframe model, preserving the local geometric similarity of the cabin floor structure, is developed and optimized to capture the low-order global dynamic characteristics of a reference airframe. …”
Get full text