Design of Cloud-Based Complex VR 3D Scene Interaction Based on Attribute Preferences by Ze Yu Yang, Yeom Jun Young

“…Concurrently, PSO is employed to optimize cloud resource allocation, managing CPU, GPU, and bandwidth to minimize latency and enhance performance efficiency. …”
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A GD-PSO Algorithm for Smart Transportation Supply Chain ABS Portfolio Optimization by Yingjia Sun, Hongfeng Ren

“…In this article, a penalty function based on graph density (GD) was introduced to the particle swarm optimization algorithm (PSO), and a GD-PSO algorithm was proposed. …”
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Research on Nonlinear Error Compensation and Intelligent Optimization Method for UAV Target Positioning by Yinglei Li, Qingping Hu, Shiyan Sun, Wenjian Ying, Xiaojia Yan

“…This study proposes an error allocation method based on the improved raccoon optimization algorithm (KYCOA) to resolve the problem of degradation of positioning accuracy due to multi-source error coupling during UAV target positioning. …”
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Rolling Bearing Dynamics Simulation Information-Assisted Fault Diagnosis with Multi-Adversarial Domain Transfer Learning by Zhe Li, Zhidan Zhong, Zhihui Zhang, Wentao Mao, Weiqi Zhang

“…Simultaneously, an improved loss function with embedded maximum mean discrepancy is designed to reduce the feature distribution gap between source and target domain data. Finally, a weight allocation mechanism for source domain and simulation domain samples is developed to promote positive transfer and suppress negative transfer. …”
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Efficient task scheduling for cloud computing: a comparative survey of state-of-the-art algorithms by Aziza Algarni

“…Multiple independent tasks need to be handled by cloud computing, and static and dynamic scheduling plays a crucial role in allocating tasks to the right resources. This is especially important in heterogeneous environments, where algorithms can improve load balancing and enhance cloud computing's efficiency. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Moreover, integrating machine learning into risk management enhances decision-making by providing precise, data-driven predictions, allowing for more effective strategies and efficient resource allocation.Future research could incorporate additional data, such as historical records, economic indicators, and internal process information, to further improve prediction accuracy. …”
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Fuzzy clustering based scheduling algorithm for minimizing the tasks completion time in cloud computing environment by Nawaf R. Alharbe

“…With its focus on fuzzy resource allocation that considers task composition and priority, BDHEFT streamlines the project schedule, ultimately reducing both execution time and costs. …”
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Developing Resilient and Expandable Adaptive Capacity Arbitration Algorithms for Future WCDMA (UMTS) Wireless Systems by M. Sajjad, S. Qaisar, A. Khan, I. Khan, S. Hussein Khan

“… The objective of this research paper is to tackle the emerging challenges associated with resource management in future WCDMA (UMTS) wireless systems by presenting resilient and expandable adaptive capacity arbitration algorithms. …”
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Multi-Link Fragmentation-Aware Deep Reinforcement Learning RSA Algorithm in Elastic Optical Network by Jing Jiang, Yushu Su, Jingchi Cheng, Tao Shang

“…Deep reinforcement learning has been extensively applied for resource allocation in elastic optical networks. However, many studies focus on link-level state analysis and rarely discuss the influence between links, which may affect the performance of allocation algorithms. …”
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QoS-aware enhanced proportional faire scheduling algorithm for real-time services in LTE networks by Mahnaz Sotoudeh Bahreyni, Vahid Sattari-Naeini

“…This paper proposes a resource scheduling downlink algorithm for LTE networks. …”
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Numerical Algorithm for Solving Market Clearing Problem in Power Electronics-Based Power Distribution Systems by Musharrat Sabah, Aaron M. Cramer, Yuan Liao

“…Market-based control is a control approach that can be used to organize resource control problems by establishing an artificial market economy for the allocation of these resources. …”
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Numerical Recognition Algorithm for Power Equipment Monitoring Based on Light-Resnet Convolutional Neural Network by Zhiheng KONG, Chong TAN, Peiyao TANG, Chengbo HU, Min ZHENG

“…This approach, leveraging the allocation of computational resources for task distribution, introduces a Light-Resnet-based numerical recognition algorithm, which enhances network training through the optimization of the D-Add loss function, enabling remote reading of electrical equipment monitoring data. …”
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A Stackelberg game based content caching algorithm in energy-harvesting small cell networks by Xueting WANG, Qi ZHU, Han HU

“…To improve the users' satisfaction of download files, a caching based resource allocation algorithm in energy-harvesting small cell networks was proposed, which was established as a Stackelberg game that jointly optimized user accessing and small cells' content updating. …”
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A dual-layer planning method based on improved MOPSO for distribution networks considering source–load temporal uncertainty by Guilian Wu, Guilian Wu, Jia Lin, Jinlin Liao

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Dynamic optimal scheduling of airport special vehicles in complex operating environment by Yonghong Liu, Min Peng, Zhihong Zhang, Jicheng Yang

“…This study focuses on the refueling vehicle as a case study and develops a dual-objective mixed integer programming model aimed at minimizing both the number of vehicles required and the total time spent on waiting, driving, and resource supplementation for special vehicles. An iterative algorithm, integrating the rolling time domain approach with the multi-chromosome band elite strategy from the non-dominated sorting genetic algorithm (NSGA-Ⅱ), is designed to solve the model. …”
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Quantum Approximate Optimization Algorithm for the Max-Cut Problem: JavaScript Programming Language Implementation by Dmytro Sapozhnyk

“…The Max-Cut issue, which involves partitioning the vertices of a graph into two subsets such that the number of edges between the subsets is maximized, is a well-known NP-hard difficulty with numerous practical applications, including network design and resource allocation. The implementation of QAOA in JavaScript is a significant step towards integrating quantum computing with modern web technologies, thus broadening access to quantum algorithms among software developers. …”
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Investigating the performance of random oversampling and genetic algorithm integration in meteorological drought forecasting with machine learning by Tahsin Baykal, Özlem Terzi, Gülsün Yıldırım, Emine Dilek Taylan

“…Abstract Drought is one of the most significant natural hazards worldwide, affecting water resources, agriculture, and socio-economic stability. …”
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A Deep Q-Learning Algorithm With Guaranteed Convergence for Distributed and Uncoordinated Operation of Cognitive Radios by Ankita Tondwalkar, Andres Kwasinski

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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…Abstract Context Understanding protein-ligand interactions is fundamental to drug design, where optimizing docking parameter selection can potentially enhance computational efficiency and resource allocation in virtual screening. While numerous algorithms exist for protein-ligand docking, achieving an optimal balance between accuracy and computational speed remains challenging. …”
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Enhancing Youbike Redistribution System: A Study on Station Recommendation Using a Genetic Algorithm by Yang-Chou Juan, Yi-Chung Chen, Wei-Ting Chen, Chieh Yang, Chia-Tzu Liu, Yi-Ci Hou, Yi-Hsuan Tsai

“…This study proposes a novel approach to optimize YouBike allocation under resource constraints. We first used K-means clustering to group stations with similar rental profiles, reducing the number of models needed. …”
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