Optimizing Berth Allocation for Maritime Autonomous Surface Ships (MASSs) in the Context of Mixed Operation Scenarios by Lixin Shen, Xueting Shu, Chengcheng Li, Tomaž Kramberger, Xiaoguang Li, Lixin Jiang

“…A large-scale simulation of the mixed-type berth allocation model is carried out using an improved simulated annealing algorithm. …”
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A cloud-metaheuristic-based framework for stochastic optimization of a hybrid wind/hydrogen based-Fuel cell system in distribution network considering uncertainty by Ali S. Alghamdi

“…An improved Fire Hawks Optimization (IFHO) algorithm is utilized in solving the optimization problem by determining the optimal installation locations and sizes of HRES components. …”
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Deploying UAV-based detection of bridge structural deterioration with pilgrimage walk optimization-lite for computer vision by Jui-Sheng Chou, Chi-Yun Liu, Pin-Jun Guo

“…This system uses UAVs to capture high-resolution images, which are then processed by the You Only Look Once (YOLO) models for instance segmentation. The YOLOv7 model, fine-tuned with the Pilgrimage Walk Optimization (PWO)-Lite algorithm, achieved the highest accuracy, recording a 65.6 % mAP50 on the testing set. …”
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Fault Diagnosis of Power Equipment Based on Improved SVM Algorithm by Youle Song, Yuting Duan, Tong Rao

“…Therefore, this study proposes an improved support vector machine model, combined with grey wolf optimization algorithm, aimed at improving the accuracy and efficiency of power equipment fault diagnosis. …”
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Improved Gradient-Based Optimizer for Modelling Thermal and Hydropower Plants by Ahmed M. Agwa, Yehya I. Mesalam, Mohamed H. Hassan, Mahmoud A. El-Dabah, Anas M. El-Sherif, Salah Kamel

“…In this research, a modified optimization algorithm called an improved gradient-based optimizer (IGBO) is deployed for the optimal extraction of TPP and HPP input-output parameters. …”
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Research on switch migration method based on minimum cost path by Yingxu LAI, Yewei PU, Jing LIU

“…In order to protect the controller,especially the controller in backbone network,from security threats and attacks,improve the security of the software-defined network (SDN) control plane,a switch migration algorithm based on minimum cost path was proposed.A load prediction module was added to the migration model,which executed a controller load prediction algorithm to obtain a load prediction matrix,and then a migration-target controller set was determined according to the load prediction matrix.The improved Dijkstra algorithm was used to determine the minimum cost path.According to the load state of the controller and the traffic priority of the switch to be migrated,the optimal migration switch set was determined.The problem of isolated nodes was solved that may occur during the migration process.The experimental results show that the migration timing of the algorithm is more reasonable,the selection of the migration controller and the target controller is more reasonable,the load balancing of the control plane is realized,the number of migrations and cost are reduced,and the performance of the controller is improved.…”
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Improved Directional Mutation Moth–Flame Optimization Algorithm via Gene Modification for Automatic Reverse Parking Trajectory Optimization by Yan Chen, Yi Chen, Yang Guo, Longda Wang, Gang Liu

“…To address this, we propose an improved directional mutation moth–flame optimization algorithm with gene modification (IDMMFO-GM). …”
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Conflict-based strategy combined integrated optimal conflict avoidance algorithm by Kejin Jia, Cheng Peng, Yun Du, Hongwei Wen, Yufei Gao, Zhe Zhang

“…Next, the low-level model of the traditional CBS algorithm is improved, transforming the path search process into two distinct algorithms with different focuses. …”
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Hybrid extreme learning machine for real-time rate of penetration prediction by Abdelhamid Kenioua, Omar Djebili, Ammar Touati Brahim

“…Abstract This study presents a comparative analysis of hybrid Extreme Learning Machine (ELM) models optimized with metaheuristic algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Grey Wolf Optimizer (GWO) for real-time Rate of Penetration (ROP) prediction in drilling operations. …”
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Research on a hybrid deep learning model based on two-stage decomposition and an improved whale optimization algorithm for air quality index prediction by Hangyu Zhou, Yongquan Yan

“…The model's hyperparameters are optimized by the Improved Whale Optimization Algorithm (IWOA), which improves search efficacy by including chaotic mapping, a nonlinear shrinkage factor, and a Levy flight strategy. …”
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Novel nonlinear wind power prediction based on improved iterative algorithm by Fu Zhen-yu, Lin Gui-quan, Tian Wei-da, Pan Zhi-hao, Zhang Wei-cong

“…To effectively improve the accuracy of wind power prediction and reduce the load on the power grid, a new nonlinear wind power prediction model based on an improved iterative learning algorithm was investigated. …”
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An Improved Soft Island Model of the Fish School Search Algorithm with Exponential Step Decay Using Cluster-Based Population Initialization by Liliya A. Demidova, Vladimir E. Zhuravlev

“…The development of new optimization algorithms or the improvement of existing ones enhances the efficiency of various fields of activity. …”
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Multijunction solar cell parameter estimation based on metaheuristic algorithms by Marwa M. Elzalabani, Doaa M. Atia, Aref Y. Eliwa, Belal A. Abou Zalam, Mahmoud S. AbouOmar

“…In addition, The Newton-Raphson Method (NRM) hybrid with meta-heuristic algorithms, or MOAs, is used to improve solution estimates, accelerate convergence rates, reduce computational costs, and enhance robustness. …”
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IGWO-MSVR model for predicting stress in coal seam during drilling process by Jian Tan, Yanfeng Geng, Liangke Xu

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Methods and Algorithms for Predictive Analytics of Time Series in Energy Consumption by Aleksandr Karmanov

“…States must minimize carbon dioxide emissions and businesses must optimize their energy costs. In this regard, improving energy efficiency plays a key role in solving the climate crisis and reducing costs for businesses. …”
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Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

“…Based on the experimental data of corrosion rates of 3C steel in different seawater environments, an improved Elman neural network model was established by using the whale optimization algorithm. …”
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ALGORITHM FOR PLANNING PROJECTS by Y. N. Kondrashov, M. O. Chashchin

“…The proposed algorithm uses a modified resource network model that allows using regular optimization algorithms in planning procedures, and provides flexibility in establishing criteria for planned decision. …”
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Computation Offloading Strategy Based on Improved Polar Lights Optimization Algorithm and Blockchain in Internet of Vehicles by Yubao Liu, Bocheng Yan, Benrui Wang, Quanchao Sun, Yinfei Dai

“…Aiming at the problems that traditional optimization algorithms tend to fall into, where local optimum in task offloading and edge computing nodes are exposed to the risk of data tampering, this paper proposes a secure offloading strategy that integrates the Improved Polar Lights Optimization algorithm (IPLO) and blockchain. …”
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UAV Path Planners in Complex Environments: A Multi-Dimensional Perturbation Based on Artificial Bee Colony by Xuzhao Chai, Guanhao Zhou, Haoyu Wang, Ping Liu, Zhongyun Liu, Chao Li, Li Yan

“…In the onlooker bee phase, the curvature-guided elite neighbor search strategy is used to prioritizes high-curvature waypoints, enhancing optimization efficiency in complex terrain. Furthermore, path costs are independently modeled in the horizontal and vertical directions. …”
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Improve Particle Swarm Optimization and Differential Evolution Algorithms Using Nash Bargaining Theory by Marziye Dadvar, Hamidreza Navidi, Hamid Haj Seyyed Javadi, Mitra Mirzarezaee

“…The proposed approach uses a coalition or cooperation model in the game theory to improve the DE and PSO algorithms. …”
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