Dynamic strategy for adaptive block size optimization in blockchain technology by Shafique Ahmed Awan, Muazzam Ali Khan Khattak, Anwar Ali Sathio, Haleem Farman, Sumaira Memon, Moustafa M. Nasralla, Ahmed Sedik

“…This study proposes a dynamic block size optimization framework for private blockchain networks using hybrid heuristic algorithms—Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO)—integrated with Merkle trees and Directed Acyclic Graphs (DAGs). …”
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Modelling and optimization for cognitive radio networks with preemption backoff mechanism by Yuan Zhao, Zhiyu Xiang, Kang Chen, Zhisheng Ye, Qi Lu

“…To assess the comprehensive performance of our proposed mechanism, we deduce various important expressions of performance indices and get the corresponding performance figures. At last, we design a cost function by compromising various performance indices and find the optimum parameter combination under the lowest system cost through the Transient Search Optimization (TSO) algorithm. …”
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Two-Stage Energy Storage Allocation Considering Voltage Management and Loss Reduction Requirements in Unbalanced Distribution Networks by Hu Cao, Lingling Ma, Guoying Liu, Zhijian Liu, Hang Dong

“…Finally, simulations are conducted using a modified IEEE-33-node system, and the results obtained using the improved beluga whale optimization algorithm show that the peak-to-valley difference of the system after the addition of energy storage decreased by 43.7% and 51.1% compared to the original system and the system with EV and PV resources added, respectively. …”
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Two-Dimensional Beam Selection by Multiarmed Bandit Algorithm Based on a Quantum Walk by Maki Arai, Tomoki Yamagami, Takatomo Mihana, Ryoichi Horisaki, Mikio Hasegawa

“…Therefore, we formulate a systematic process for beam selection employing the MAB algorithm rooted in QW principles. We derive the optimal parameters of this method to maximize achievable channel capacity. …”
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Deep Reinforcement Learning for Optimal Replenishment in Stochastic Assembly Systems by Lativa Sid Ahmed Abdellahi, Zeinebou Zoubeir, Yahya Mohamed, Ahmedou Haouba, Sidi Hmetty

“…This study presents a reinforcement learning–based approach to optimize replenishment policies in the presence of uncertainty, with the objective of minimizing total costs, including inventory holding, shortage, and ordering costs. …”
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Enhancing adaptive beamforming by enhanced MUSIC algorithm for urban environments in O-RAN architecture by Mustafa Mayyahi, Jordi Mongay Batalla, Constandinos X. Mavromoustakis

“…This enhancement reduces the latency associated with beamforming adjustments, improves AoA accuracy, and optimizes beam direction preemptively, thereby improving network efficiency and user connectivity. …”
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DP-YOLO: A Lightweight Real-Time Detection Algorithm for Rail Fastener Defects by Lihua Chen, Qi Sun, Ziyang Han, Fengwen Zhai

“…To enable accurate and efficient real-time detection of rail fastener defects under resource-constrained environments, we propose DP-YOLO, an advanced lightweight algorithm based on YOLOv5s with four key optimizations. …”
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LI-YOLO: An Object Detection Algorithm for UAV Aerial Images in Low-Illumination Scenes by Songwen Liu, Hao He, Zhichao Zhang, Yatong Zhou

“…Compared with other current algorithms, LI-YOLO improves the mAP 50 by 3.1% on the DroneVehicle dataset and 6.9% on the LLVIP dataset. …”
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Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema by Anwesa Mondal, Apurba Nandi, Subhasish Pramanik, Lakshmi Kanta Mondal

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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

“…In another study, Akbari and Yazdanian (2023) applied machine learning algorithms to determine optimal thresholds for operational loss severity data, classifying the data and estimating the capital required to cover operational risk by integrating severity and frequency distribution functions with Monte Carlo simulation. …”
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Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…This research utilizes swarm intelligence algorithms—Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and hybrid PSO-ACO-to optimize energy efficiency and thermal comfort in smart building HVAC systems. …”
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Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…Aiming at the problem of drought forecasting accuracy in a short time scale, this study proposed a drought forecasting model named VMD-JAYA-Informer based on Variational Mode Decomposition (VMD) and the JAVA optimization algorithm to improve the Informer model. …”
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Quantifying and optimizing single-molecule switching nanoscopy at high speeds. by Yu Lin, Jane J Long, Fang Huang, Whitney C Duim, Stefanie Kirschbaum, Yongdeng Zhang, Lena K Schroeder, Aleksander A Rebane, Mary Grace M Velasco, Alejandro Virrueta, Daniel W Moonan, Junyi Jiao, Sandy Y Hernandez, Yongli Zhang, Joerg Bewersdorf

“…Recent advances in this technique have greatly accelerated the data acquisition speed and improved the temporal resolution of super-resolution imaging. …”
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Optimal entanglement distribution within a multi-ring topology by B. C. Ciobanu, T. A. Calafeteanu, A. B. Popa, R. Tătăroiu, P. G. Popescu

“…We propose algorithms that solve the problem of entanglement distribution in terms of optimal time needed to satisfy a set of entanglement resupply requests with given network resources, as well as the problem of optimal resources in order to satisfy a set of entanglement resupply requests within a single entanglement transmission and measurement step. …”
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Driving Strategy Using an Improved Ant Colony System for Energy-Efficient Train by Chengda Yang, Kun Miao, Jieyuan Wang

“…Optimal energy-efficient train operation optimization is one of the widely studied areas in transportation science, which can significantly reduce energy consumption that accounts for a large proportion of operating costs. …”
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Microgrid Load Forecasting Based on Improved Long Short-Term Memory Network by Qiyue Huang, Yuqing Zheng, Yuxuan Xu

“…In this paper, a load-forecasting algorithm for microgrid based on improved long short-term memory neural network (LSTM) is proposed. …”
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Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs by Kaifeng Geng, Chunming Ye, Zhen hua Dai, Li Liu

“…This paper proposes an improved multiobjective ant lion optimization (IMOALO) algorithm to solve the RHFSP with the objectives of minimizing the makespan and energy consumption cost under Time-of-Use (TOU) electricity tariffs. …”
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Optimization of Multiperiod Mixed Train Schedule on High-Speed Railway by Wenliang Zhou, Junli Tian, Jin Qin, Lianbo Deng, TangJian Wei

“…And its heuristic algorithm is designed to optimize the multiperiod mixed train schedule beginning with generating an initial solution by scheduling all types of train type by type and then repeatedly improving their periodic schedules until the objective value cannot be reduced or the iteration number reaches its maximum. …”
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An Analytic Policy Gradient-Based Deep Reinforcement Learning Motion Cueing Algorithm for Driving Simulators by Xiaowei Huang, Xuhua Shi, Peiyao Wang, Hongzan Xu, Xiaojun Tang, Gaoran Zhang

“…Unlike the online optimization employed in MPC, this algorithm as an offline optimization method, providing substantial computational advantages when integrated into the driving simulator. …”
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A comparative study of the performance of ten metaheuristic algorithms for parameter estimation of solar photovoltaic models by Adel Zga, Farouq Zitouni, Saad Harous, Karam Sallam, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…The algorithms evaluated include the Crayfish Optimization Algorithm, the Golf Optimization Algorithm, the Coati Optimization Algorithm, the Crested Porcupine Optimizer, the Growth Optimizer, the Artificial Protozoa Optimizer, the Secretary Bird Optimization Algorithm, the Mother Optimization Algorithm, the Election Optimizer Algorithm, and the Technical and Vocational Education and Training-Based Optimizer. …”
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