A hybrid machine learning algorithm approach to predictive maintenance tasks: A comparison with machine learning algorithms by Jorge Paredes, Danilo Chávez, Ramiro Isa-Jara, Diego Vargas

“…Additionally, the hybrid approach enables early predictions of approximately 17 cycles and late predictions of only 2%, while other learning algorithms, such as linear regression, do not make early predictions but 100% of their predictions are late. …”
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Microcrack feature extraction method for chaotic optical surface of silicon nitride ceramic bearing roller based on multi-scale wavelet transform enhancement and optimized PSO-FCM... by Yi Jiang, Mengtao Tang, Wenjie Dong, Guoxing Tang, Weiwen Hu, Jiao Li

“…To address the issue of chaotic optical gradient feature and non-target interference factors affecting the feature extraction effect of chaotic optical surface microcracks in silicon nitride ceramic bearing rollers, an algorithm for extracting microcrack features from chaotic optical surfaces of silicon nitride ceramic bearing rollers based on multi-scale wavelet transform enhancement and optimized PSO-FCM coupling is proposed. …”
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Optimizing Fuel Efficiency and Emissions of Marine Diesel Engines When Using Biodiesel Mixtures Under Diverse Load/Temperature Conditions: Predictive Model and Comprehensive Life C... by Kwang-Sik Jo, Kyeong-Ju Kong, Seung-Hun Han

“…Marine transportation contributes approximately 2.5% of global greenhouse gas emissions. While previous studies have examined biodiesel effects on automotive engines, research on marine applications reveals critical gaps: (1) existing studies focus on single-parameter analysis without considering the complex interactions between biodiesel ratio, engine load, and operating conditions; (2) most research lacks comprehensive lifecycle assessment integration with real-time operational data; (3) previous optimization models demonstrate insufficient accuracy (R² < 0.80) for practical marine applications; and (4) no adaptive algorithms exist for dynamic biodiesel ratio adjustment based on operational conditions. …”
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Chiến lược tối ưu đa mục tiêu nhằm tăng cường hiệu suất hệ thống điện phân phối khi tích hợp nguồn điện phân tán by Tôn Ngọc Triều, Lê Minh Phong, Lê Minh Tân

“…Thuật toán Raccoon Optimization Algorithm (ROA) là một phương pháp tối ưu meta-heuristic mới, được áp dụng và đối chiếu với các thuật toán như Firefly Algorithm (FA), Moth Flame Optimization (MFO), Salp Swarm Algorithm (SSA), và Whale Optimization Algorithm (WOA). …”
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Adversarial Range Gate Pull-Off Jamming Against Tracking Radar by Yuanhang Wang, Yi Han, Yi Jiang

“…The PSO-ER algorithm searches for optimal jamming strategies while utilizing a localized simulation of the tracking radar to evaluate the effectiveness of candidate jamming strategies. …”
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Multilevel Constrained Bandits: A Hierarchical Upper Confidence Bound Approach with Safety Guarantees by Ali Baheri

“…We propose the HC-UCB (hierarchical constrained upper confidence bound) algorithm to solve the HCB problem. The algorithm uses confidence bounds within a hierarchical setting to balance exploration and exploitation while respecting constraints at all levels. …”
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Intelligent End-Edge Computation Offloading Based on Lyapunov-Guided Deep Reinforcement Learning by Xue Feng, Chi Xu, Xi Jin, Changqing Xia, Jing Jiang

“…To address the end-edge computation offloading challenge in the multi-terminal and multi-server environment, this paper proposes an intelligent computation offloading algorithm based on Lyapunov optimization and deep reinforcement learning. …”
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A DDQN-Guided Dual-Population Evolutionary Multitasking Framework for Constrained Multi-Objective Ship Berthing by Jinyou Mou, Qidan Zhu

“…Simulations on the CSAD vessel model demonstrate that this framework outperforms baseline algorithms such as evolutionary multitasking constrained multi-objective optimization (EMCMO), DQN, Q-learning, and non-dominated sorting genetic algorithm II (NSGA-II), achieving superior efficiency and stability while maintaining the required berthing angle. …”
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Research on Impact of Planned Path Length and Yaw Cost on Collaborative Search of Unmanned Aerial Vehicle Swarms by Heng Zhang, Wenyue Meng, Yanan Liu, Guanyu Liu, Jian Zhang

“…To address the unclear impacts of a planned path length and yaw cost on search performance in large-scale Unmanned Aerial Vehicle (UAV) swarm collaborative search scenarios under complex and dynamic environments, a path grid determination algorithm is proposed, transforming the path-planning problem into an optimal waypoint selection problem, enabling UAVs to make rapid decisions using the Particle Swarm Optimization (PSO) algorithm. …”
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Multi-criteria decision model for multicircular flight control of unmanned aerial vehicles through a hybrid approach by Noorulden Basil, Hamzah M. Marhoon, Bayan Mahdi Sabbar, Abdullah Fadhil Mohammed, Osamah Albahri, Ahmed Albahri, Abdullah Alamoodi, Iman Mohamad Sharaf, Amare Merfo Amsal, Mahrous Ahmed, Enas Ali, Sherif S. M. Ghoneim

“…The proposed algorithm combines the strengths of particle swarm optimization (PSO) and the ant lion optimizer (ALO), which are enhanced by the Eagle strategy to systematically fine-tune the FOPID controller parameters. …”
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A decision-theoretic framework for wastewater treatment performance assessment based on a fuzzy parameterized fuzzy hypersoft set approach by Muhammad Haris Saeed, Fatima Razaq, Muhammad Saeed, Muhammad Salman Habib, Seung-June Hwang

“…With proper fuzzy parameterization of each sub-attribute, novel specialized FPFHSS based Technique of Ordered Preference Similar to Ideal Solution (TOPSIS) and Multi-Objective Optimization on the basis of a Ratio Analysis (MULTIMOORA) approaches are developed that provide a versatile analysis in addition to the newly developed algorithm. …”
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A Swarm-Based Multi-Objective Framework for Lightweight and Real-Time IoT Intrusion Detection by Hessah A. Alsalamah, Walaa N. Ismail

“…MOOIDS-IoT combines a Genetic Algorithm (GA)-based feature selection technique with a multi-objective Particle Swarm Optimization (PSO) algorithm. …”
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Occupant-Centric Visual Comfort Assessment and Optimization of Passive Solar Façade Shading Systems through View-Based Analysis of Daylight Glare Probability, View Content, and Spa... by Martin Ivanov, Jun Sato

“…Two experimental studies validate the approach: the first systematically evaluates multiple predefined shading patterns to identify optimal characteristics, while the second demonstrates that algorithmic optimization of highly irregular shading configurations can simultaneously improve multiple visual comfort metrics, significantly outperforming regular shading patterns in terms of glare reduction, view preservation, and spatial frequency performance.…”
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Real time weed identification with enhanced mobilevit model for mobile devices by Xiaoyan Liu, Qingru Sui, Zhihui Chen

“…Abstract Deep learning model optimization have notably enhanced weed identification accuracy. …”
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Microservice Workflow Scheduling with a Resource Configuration Model Under Deadline and Reliability Constraints by Wenzheng Li, Xiaoping Li, Long Chen, Mingjing Wang

“…Additionally, we propose a reliability microservice workflow scheduling algorithm (RMWS), which incorporates heuristic leasing and deployment strategies to ensure reliability while reducing cloud resource leasing cost. …”
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A Biased–Randomized Iterated Local Search with Round-Robin for the Periodic Vehicle Routing Problem by Juan F. Gomez, Antonio R. Uguina, Javier Panadero, Angel A. Juan

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The Robust Steiner Team Orienteering Problem with Decreasing Priorities under budgeted uncertainty by Lucas Assunção, Andréa Cynthia Santos

“…R-STOP-DP is a variation of the vehicle routing problem with location priorities that applies robust optimization to model the variability on service times incurred by visiting locations. …”
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STARMAP: Spaceborne Target Acquisition Radar With Meta-RL Assisted Placement by Alireza Famili, Shihua Sun, Tolga Atalay, Angelos Stavrou

“…To address this, we have developed an advanced meta-reinforcement learning (meta-RL) algorithm, enhancing a double deep Q-network (DDQN) to optimize receiver placement. …”
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Nondestructive detection and classification of impurities-containing seed cotton based on hyperspectral imaging and one-dimensional convolutional neural network by Yeqi Fei, Zhenye Li, Tingting Zhu, Zengtao Chen, Chao Ni

“…By fusing band combination optimization with deep learning, this study aims to achieve more efficient and accurate detection of film impurities in seed cotton on the production line. …”
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Secure THz Communication in 6G: A Two-Stage DRL Approach for IRS-Assisted NOMA by Muhammad Shahwar, Manzoor Ahmed, Touseef Hussain, Muhammad Sheraz, Wali Ullah Khan, Teong Chee Chuah

“…Utilizing the deep deterministic policy gradient (DDPG) algorithm, we introduce a two-stage policy learning approach designed to optimize secrecy energy efficiency (SEE) while ensuring secure communication, even in the presence of multiple eavesdroppers (Eves). …”
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