A Novel Forecasting System with Data Preprocessing and Machine Learning for Containerized Freight Market by Yonghui Duan, Xiaotong Zhang, Xiang Wang, Yingying Fan, Kaige Liu

“…Additionally, variational mode decomposition (VMD) technique is employed to decompose the time series in a rolling manner, effectively avoiding data leakage while extracting significant features. In the forecasting stage, the cheetah optimization algorithm (COA) optimizes the key parameters of the extreme gradient boosting (XGBoost) model, enhancing forecasting accuracy. …”
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DASL: An Index for Enhancing Tail Latency, Microarchitecture Friendliness, and Restructuring Overhead by Hojin Shin, Gunhee Choi, Bryan S. Kim, Seehwan Yoo, Jongmoo Choi

“…In addition, it is flexible in inserting and deleting data, while avoiding the restructuring overhead of tree-based structures. …”
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Economic and environmental power dispatch for energy management systems applied to microgrids with wind energy resources and battery energy storage systems by Jhon Montano, John E. Candelo-Becerra, Cristian Escudero-Quintero, Juan Pablo Guzmán

“…To solve this problem, four metaheuristic optimization algorithms were implemented: Enhanced Prairie Dog Optimization (EPDO), Salp Swarm Algorithm (SSA), Generalized Normal Distribution Optimization (GNDO), and Crow Search Algorithm (CSA). …”
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Solar Irradiance Prediction Method for PV Power Supply System of Mobile Sprinkler Machine Using WOA-XGBoost Model by Dan Li, Jiwei Qu, Delan Zhu, Zheyu Qin

“…Based on meteorological data provided by ten typical radiation stations uniformly distributed nationwide, an Extreme Gradient Boosting (XGBoost) model optimized using the Whale Optimization Algorithm (WOA) is developed to predict solar radiation. …”
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Optimizing sustainable blended concrete mixes using deep learning and multi-objective optimization by Rupesh Kumar Tipu, Preeti Rathi, Kartik S. Pandya, Vijay R. Panchal

“…The Multi-Objective Particle Swarm Optimization (MOPSO) algorithm finds multiple optimal solutions which simultaneously optimize three competing objectives that include strength maximization and cost minimization and cement reduction. …”
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Facility location problem for senior centers in an upcoming super-aging society by Eun Hak Lee, Jonghwa Jeong

“…This study aims to address the facility location problem for senior centers in upcoming super-aging societies. An optimization model is developed using a genetic algorithm to determine the optimal locations of senior centers. …”
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Comparative analysis of water network minimization in industrial processes: Regeneration vs. non-regeneration methods by Khalifa Azza Mohamed, Elsayed Nadia Ali, Awad Mostafa

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Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification by Abeer saber, Esraa Hassan, Samar Elbedwehy, Wael A. Awad, Tamer Z. Emara

“…MobileNetV2, ResNet50, and EfficientNet-B0 hyperparameters have been optimized using a modified grey wolf optimization (GWO) approach for better performance. …”
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Configurational Comparison of a Binary Logic Transmission Unit Applicable to Agricultural Tractor Hydro-Mechanical Continuously Variable Transmissions and Its Wet Clutch Optimizati... by Wenjie Li, Zhun Cheng, Mengchen Yang

“…Under light-load conditions, the optimized GRNN reduced total relative error by 39.6%, while under heavy-load conditions, it achieved a 61% reduction. …”
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Optimal Design for a Novel Compliant XY Platform Integrated with a Hybrid Double Symmetric Amplifier Comprising One-Lever and Scott–Russell Mechanisms Arranged in a Perpendicular S... by Minh Phung Dang, Anh Kiet Luong, Hieu Giang Le, Chi Thien Tran

“…The pseudo-rigid body model (PRBM), Lagrangian approach, finite element analysis (FEA), and Firefly optimization algorithm were employed to develop, verify, and optimize the quality response of the new positioner. …”
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Fleet Size and Mix Vehicle Routing Problem (FSMVRP), Adapted Large Neighbourhood Search Heuristic Optimization ProposalWith a Plant-capacity and Multi-day Planning Algorithm: A Liv... by Alperen Ekrem Çelikdin

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Adaptive Bacterial Foraging Optimization by Hanning Chen, Yunlong Zhu, Kunyuan Hu

“…Bacterial Foraging Optimization (BFO) is a recently developed nature-inspired optimization algorithm, which is based on the foraging behavior of E. coli bacteria. …”
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Congestion Influence on Optimal Bidding in a Competitive Electricity Market using Particle Swarm Optimization by OICC Press Authors

“…In this paper, the bidding strategy problem with congestion management is modeled as an optimization problem and solved using Particle Swarm Optimization (PSO).  …”
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Application of Genetic Algorithms in Nonlinear Heat Conduction Problems by Muhammad Bilal Kadri, Waqar A. Khan

“…Genetic algorithms are employed to optimize dimensionless temperature in nonlinear heat conduction problems. …”
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FM‐YOLOv8:Lightweight gesture recognition algorithm by Fanghai Li, Xitai Na, Jinshuo Shi, Qingbin Sun

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Routing and Scheduling in Time-Sensitive Networking by Evolutionary Algorithms by Zengkai Wang, Weizhi Liao, Xiaoyun Xia, Zijia Wang, Yaolong Duan

“…In this paper, we propose a novel routing and scheduling approach for TSN based on evolutionary algorithm. Specifically, we introduce a flow grouping method that leverages the greatest common divisor to optimize flow aggregation. …”
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Energy consumption optimization scheme in UAV-assisted MEC system based on optimal SIC order by Wei JI, Xuxin YANG, Fei LI, Ting LI, Yan LIANG, Yunchao SONG

“…In uplink non-orthogonal multiple access (NOMA)-based unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system, the successive interference cancellation (SIC) order of NOMA became a bottleneck limiting the transmission performance of task offload in uplink link.To reduce the energy consumption of the system, the SIC order was discussed and the optimal SIC order based on channel gain and task delay constraint was proposed.The optimization problem of minimizing the system energy consumption was proposed based on the optimal SIC order while satisfying the constraints of the given task delay of the device, the maximum transmit power constraint of the device, and the UAV trajectory.Since the problem was a complex non-convex problem, an alternating optimization method was adopted to solve the optimization problem to achieve power allocation and UAV trajectory optimization.A low-complexity algorithm based on matching theory was proposed to obtain the optimal device grouping in different time slots.Simulation results show that the optimal SIC order can realize smaller system energy consumption under the same task delay constraint compared with other SIC order, the proposed low-complexity device grouping algorithm can obtain the optimal device grouping.…”
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Energy consumption optimization scheme in UAV-assisted MEC system based on optimal SIC order by Wei JI, Xuxin YANG, Fei LI, Ting LI, Yan LIANG, Yunchao SONG

“…In uplink non-orthogonal multiple access (NOMA)-based unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system, the successive interference cancellation (SIC) order of NOMA became a bottleneck limiting the transmission performance of task offload in uplink link.To reduce the energy consumption of the system, the SIC order was discussed and the optimal SIC order based on channel gain and task delay constraint was proposed.The optimization problem of minimizing the system energy consumption was proposed based on the optimal SIC order while satisfying the constraints of the given task delay of the device, the maximum transmit power constraint of the device, and the UAV trajectory.Since the problem was a complex non-convex problem, an alternating optimization method was adopted to solve the optimization problem to achieve power allocation and UAV trajectory optimization.A low-complexity algorithm based on matching theory was proposed to obtain the optimal device grouping in different time slots.Simulation results show that the optimal SIC order can realize smaller system energy consumption under the same task delay constraint compared with other SIC order, the proposed low-complexity device grouping algorithm can obtain the optimal device grouping.…”
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Error Covariance Analyses for Celestial Triangulation and Its Optimality: Improved Linear Optimal Sine Triangulation by Abdurrahim Muratoglu, Halil Ersin Söken, Uwe Soergel

“…While current methods like Linear Optimal Sine Triangulation (LOST) provide statistically optimal solutions for position estimation using multiple celestial body observations, their performance can be compromised by suboptimal measurement pair selection. …”
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DMS Algorithm in the Application of the Map/Reduce Tasks Schedule by PEI Shu-jun, KONG De-kai, MIAO Hui

“…The whole efficiency of traditional task scheduling algorithms is low under the cloud environment, In order to improve the whole efficiency of the task scheduling, this article based on Map/Reduce presents a Difference Matrix Scheduling tasks schedule algorithm based on processing time. …”
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