Machine Learning-Driven Prediction of CO₂ Solubility in Brine: A Hybrid Grey Wolf Optimizer (GWO)-Assisted Gaussian Process Regression (GPR) Approach by Seyed Hossein Hashemi, Farshid Torabi, Paitoon Tontiwachwuthikul

“…In this study, Gaussian Process Regression (GPR) with eight different kernels was optimized using the Grey Wolf Optimizer (GWO) algorithm to model this important phase behavior. …”
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Dynamic SDN controller placement based on latency in LEO satellite network by Zhenzhen HAN, Guofeng ZHAO, Chuan XU, Wentao ZHOU, Yangyang ZHOU

“…In view of the problem of large network latency when the controller synchronized information to maintain the global network view,the latency-based SDN controller on-demand placement scheme was proposed.Firstly,the satellite subnet division method based on redundant coverage was designed according to the relative velocity of satellite and terminal.Then,the controller placement model was established by analyzing the response latency of the satellite distributed control.Finally,the controller placement problem was transformed into the soft capacitated facility location problem,and the approximation algorithm was designed to solve the model.The experimental results show that the proposed scheme can optimize network latency while meeting networking coverage demands.…”
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Online English teaching resource recommendation method design based on LightGCNCSCM by Jing Tang

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An automated adaptive trading system for enhanced performance of emerging market portfolios by Cristiana Tudor, Robert Sova

“…Abstract One of the most notable developments in the asset management industry in recent decades has been the growth of algorithmic trading. At the same time, significant structural changes in the industry have occurred, with passive investing gaining momentum. …”
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Exploring the Impact of Artificial Intelligence on Healthcare Management: A Combined Systematic Review and Machine-Learning Approach by Vito Santamato, Caterina Tricase, Nicola Faccilongo, Massimo Iacoviello, Agostino Marengo

“…The scientific novelty of the study lies in its integrated approach, combining systematic review and predictive algorithms to provide a comprehensive understanding of AI’s role in improving healthcare management across different contexts. …”
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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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Grid Integration of PV Systems With Advanced Control and Machine Learning Strategies by Venkata Reddy Kota, Bapayya Naidu Kommula, Asif Afzal, Mohammad Asif, Liew Tze Hui

“…The primary objective is to optimize voltage output from PV system while concurrently maximizing power using a novel Modified Zeta-Cuk converter, coupled with Hybrid Maximum Power Point Tracking (MPPT) algorithm combining Incremental Conductance and Bat Optimization Algorithm (InC-BOA). …”
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RLEAFS: Reinforcement Learning-Based Energy Aware Forwarding Strategy for NDN-Based IoT Networks by Naeem Ali Askar, Adib Habbal

“…To address these challenges, we propose Reinforcement Learning-based Energy-Aware Forwarding Strategy (RLEAFS), a novel strategy for NDN-based IoT communications that leverages reinforcement learning to optimize forwarding decisions. Our Strategy integrates Q learning algorithm into path selection procedure, focusing on minimizing energy consumption and extending network lifetime while maintaining efficient data delivery. …”
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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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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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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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Enhanced securities investment strategy using ISSA–SVM: a hybrid model combining adaptive moving average, support vector machine, and multi-strategy sparrow search algorithm for im... by Wei Ni, Qingqing Chen, Xiaochen Guo, Yanan Liu

“…The strategy incorporates three key innovations: (1) an AMA algorithm that dynamically adjusts smoothing coefficients to market conditions, improving response speed and accuracy across different market environments. (2) SVM classification for trend prediction, leveraging its robust nonlinear classification capabilities. (3) a Multi-Strategy Sparrow Search Algorithm that optimizes multiple parameters and strategy combinations while avoiding local optima. …”
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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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Bio-Inspired Observability Enhancement Method for UAV Target Localization and Sensor Bias Estimation with Bearing-Only Measurement by Qianshuai Wang, Zeyuan Li, Jicheng Peng, Kelin Lu

“…The nonlinear constrained multi-objective whale optimization algorithm achieves minimal values for both generational distance and inverted generational distance, demonstrating superior convergence and diversity characteristics.…”
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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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The P Balasubramaniam Award-2024 Singapore Orthopaedic Association Annual Scientific Meeting Award: Novel artificial intelligence algorithm for soft tissue balancing and bone cuts... by Matthew Song Peng Ng, Ryan Wai Keong Loke, Melvin Kian Loong Tan, Yau Hong Ng, Zi Qiang Glen Liau

“…Methods We developed a novel AI computational algorithm to optimize rTKA implant positioning in three-dimensional space. …”
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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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