AE-BPNN: autoencoder and backpropagation neural network-based model for lithium-ion battery state of health estimation by Abdullah Ahmed Al-Dulaimi, Muhammet Tahir Guneser, Raghad Al-Shabandar, Yeonghyeon Gu, Muhammad Syafrudin, Norma Latif Fitriyani

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A Blockchain-Based Collaborative Storage Scheme for Roadside Unit Clusters in Social Internet of Vehicles by Dai Hou, Lan Wei, Lei Zheng, Geng Wu, Jiaxing Hu, Chenxi Dong, Xinru Li, Kai Peng

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Towards ML Models’ Recommendations by Lara Kallab, Elio Mansour, Richard Chbeir

“…A prominent way to achieve this is machine learning (ML), which optimizes system performance by employing learning algorithms to create models based on data and its inherent patterns. …”
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AI-Driven Fire Detection and Suppression System with Real-Time Remote Monitoring by Metahri Dhiyaeddine, Dekar Amina, SettingsKadi Halima Bouchra

“…Our project aims to develop an intelligent solution using artificial intelligence AI to optimize these processes. …”
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Behavior Modeling and Bio-Hybrid Systems: Using Reinforcement Learning to Enhance Cyborg Cockroach in Bio-Inspired Swarm Robotics by Le Minh Triet, Nguyen Truong Thinh

“…Bio-inspired swarm robotics is an emerging field at the intersection of biology, robotics, and artificial intelligence, offering novel capabilities by integrating living organisms with robotic systems. …”
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Short-term PV power prediction based on meteorological similarity days and SSA-BiLSTM by Yikang Li, Wei Huang, Keying Lou, Xizheng Zhang, Qin Wan

“…The experiments were conducted with historical data from a PV power plant in Xinjiang, and also compared with existing prediction algorithms.The results show that the accuracy of PV power prediction in different weather conditions is 33.1 %, 31.9 % and 24.1 % higher than that under the same intelligent optimization algorithm and different neural networks, the accuracy of PV power prediction in different weather conditions is 27.9 %, 24.7 % and 18.0 % higher than that under the different intelligent algorithms and same neural network. …”
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Reinforcement Learning With Selective Exploration for Interference Management in mmWave Networks by Son Dinh-van, van-Linh Nguyen, Berna Bulut Cebecioglu, Antonino Masaracchia, Matthew D. Higgins

“…To tackle the high-variance rewards caused by narrow antenna beamwidths, we introduce a selective exploration method to guide the agent towards more intelligent exploration. Our proposed algorithms are well-suited for scenarios where beamforming vectors require control in either a discrete domain, such as a codebook, or in a continuous domain. …”
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Trajectory Planning Method for Formation Rendezvous of Underactuated Multi-UUV Under Multiple Constraints by Qingzhe Wang, Da Xu, Xiaoran Liu, Gengshi Zhang, Zhao Han

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A Comprehensive Survey on Machine and Deep Learning for Optical Communications by Mohammad Ali Amirabadi, S. Alireza Nezamalhosseini, Mohammad Hossein Kahaei, Lawrence R. Chen

“…Specific emphasis is placed on identifying how these algorithms enhance system performance and optimization. …”
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Trail-Using Ant Behavior Based Energy-Efficient Routing Protocol in Wireless Sensor Networks by Soon-gyo Jung, Byungseok Kang, Sanggil Yeoum, Hyunseung Choo

“…Ant Colony Optimization (ACO) algorithm is one of the popular algorithms in SI. …”
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Enhancing stock index prediction: A hybrid LSTM-PSO model for improved forecasting accuracy. by Xiaohua Zeng, Changzhou Liang, Qian Yang, Fei Wang, Jieping Cai

“…PSO-LSTM model leveraging PSO's efficient swarm intelligence and strong optimization capabilities is proposed in this article. …”
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Balancing Predictive Performance and Interpretability in Machine Learning: A Scoring System and an Empirical Study in Traffic Prediction by Fabian Obster, Monica I. Ciolacu, Andreas Humpe

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UASI-PRECISE CONTROL OF AN AUTONOMOUS MOBILE ROBOT by V.R. Aleksandrov, N.V. Azarnov, A.A. Schetkin, A.P. Kushnir, R.M. Оgoreltcev

“…Conclusions. The proposed intelligent control algorithms allow reducing the cost of a logistics project based on autonomous robots and abandoning a number of expensive software. …”

Human-based metaheuristics and non-parametric learning for groundwater-prone area mapping by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Seyedeh Zeinab Shogrkhodaei, Biswajeet Pradhan, Soo-Mi Choi

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Investigating Transfer Learning in Noisy Environments: A Study of Predecessor and Successor Features in Spatial Learning Using a T-Maze by Incheol Seo, Hyunsu Lee

“…By offering insights into the optimal hyperparameter configurations, this study contributes to the development of more adaptive and robust learning algorithms, paving the way for future explorations in artificial intelligence and neuroscience.…”
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Research Progress of Finite Element Technology in Wood Processing by Maosen Wang, Lin Yang

“…It highlights challenges such as model accuracy and algorithm optimization, suggesting that continuous improvements in FEA models and algorithms can further enhance processing efficiency and product quality. …”
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IDLEWiSE by Chiara Fusar Bassini, Leonard Hackel, Thorren Kirschbaum

“…This paper outlines an optimization tool using efficient machine-learning algorithms like decision trees to learn optimal shutdown policies online. …”
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Myoelectric Control in Rehabilitative and Assistive Soft Exoskeletons: A Comprehensive Review of Trends, Challenges, and Integration with Soft Robotic Devices by Alejandro Toro-Ossaba, Juan C. Tejada, Daniel Sanin-Villa

“…Additionally, we identify persistent challenges such as EMG signal variability, computational complexity, and the real-time adaptability of control algorithms, which limit clinical implementation. By interpreting recent trends, this review highlights the need for improved EMG acquisition techniques, robust adaptive control frameworks, and enhanced real-time learning to optimize human-exoskeleton interaction. …”
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Design and performance analysis of wear-resistant micro-groove cutting tool: Numerical simulation and experimental study by Feilong Du, Fukuan Chen, Tao Zhou, Hongfei Yao, Xuefeng Zhao, Dongwei Zhu, Lin He

“…This investigation establishes a novel computational framework integrating finite element modeling (FEM), machine learning (ML)-based predictive analysis, and multi-objective genetic algorithm (GA) optimization for micro-groove tool design. …”
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Coal mining equipment lifecycle management system architecture and key technology by Yihui PANG, Jinglong BI, Pengzhe YUAN, Baofu ZHAO, Ziwei DING

“…An optimization algorithm and software platform for comprehensive mining equipment selection were developed, and a method for constructing a series spectrum and coding system for coal mining equipment was proposed. …”
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