Improved security for IoT-based remote healthcare systems using deep learning with jellyfish search optimization algorithm by Faris Kateb, Mahmoud Ragab, Felwa Abukhodair, Omar Ahmed Abdulkader, Louai A. Maghrabi, Sami Saeed Binyamin, Mohammed Khaled Al-Hanawi

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Improved Monthly Runoff Prediction of OSELM Based on Secondary Decomposition Technique and Optimization of Ten "Bird" Swarm Algorithms by DENG Zhiyu, CUI Dongwen

“…To improve the accuracy of monthly runoff time series prediction and enhance the performance of online sequential extreme learning machine (OSELM) prediction, ten "bird" swarm algorithms were compared and validated for optimization, including satin bowerbird optimizer (SBO)/Harris hawks optimization (HHO)/seagull optimization algorithm (SOA)/African vultures optimization algorithm (AVOA)/coot optimization algorithm (COOT)/pelican optimization algorithm (POA)/eagle perching optimization (EPO)/osprey optimization algorithm (OOA). …”
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Improved Lyrebird optimization for multi microgrid sectionalizing and cost efficient scheduling of distributed generation by Karthik Nagarajan, Arul Rajagopalan, Mohit Bajaj, Valliappan Raju, Vojtech Blazek, Lukas Prokop

“…This paper introduces the Improved Lyrebird Optimization Algorithm (ILOA) for optimal sectionalizing and scheduling of multi-microgrid systems, aiming to minimize generation costs and active power losses while ensuring system reliability. …”
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A Bi-Level Capacity Optimization Method for Hybrid Energy Storage Systems Combining the IBWO and MVMD Algorithms by Qiaoqiao Xing, Shidong Li, Da Qiu, Yang Long, Qinyi Liao, Xiangjin Yin, Yunxiang Li, Kai Qian

“…The outer layer minimizes the annual total cost through the application of an Improved Beluga Whale Optimization (IBWO) algorithm, which is enhanced by strategies including the reverse elitism strategy, horizontal and vertical crossover operations, and a whirlwind scavenging strategy to improve performance. …”
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Generic optimal power flow solution associated with technical improvements and emission reduction by multi-objective ARO algorithm by Amlak Abaza, Ragab A. El-Sehiemy, Zakeria Elbarabry, Asmaa F. Barakat

“…Artificial rabbits’ optimization (ARO) is developed to find the optimal OPF framework solution. …”
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Road damage detection based on improved YOLO algorithm by Luyao Ma, Ming Chen

“…The dual-branch attention mechanisms enhance feature representation in channel and spatial dimensions, while the GIoU loss optimizes bounding box regression—yielding notable improvements, particularly in small object detection and bounding box localization accuracy. …”
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An Operation Optimization Strategy of the Combined Power Generation System with Wind Power & Pumped Storage Based on Improved Whale Algorithm by LI Kecheng, YANG Ning

“…In order to solve the model, based on the basic whale optimization algorithm, a multi-objective whale optimization algorithm is developed by adding external population and leader selection mechanism, and the control parameter in the algorithm is improved to obtain an improved multi-objective whale optimization algorithm. …”
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A Novel Exploration Stage Approach to Improve Crayfish Optimization Algorithm: Solution to Real-World Engineering Design Problems by Harun Gezici

“…In order to compensate these shortcomings, this study proposes an Improved Crayfish Optimization Algorithm (ICOA) that designs the competition stage with three modifications: (1) adaptive step length mechanism inversely proportional to the number of iterations, which enables exploration in early iterations and exploitation in later stages, (2) vector mapping that increases stochastic behavior and improves efficiency in high-dimensional spaces, (3) removing the X_shade parameter in order to abstain from early convergence. …”
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Enhanced zebra optimization algorithm for sustainable combined economic and emission dispatch in power systems by Ahmed Arkwazee, Rana Abttan

“…Experimental results show that IMZOA significantly reduces costs and emissions compared to established algorithms like LM and SA, and improved methods such as asinhCAOA, RLADE, and the standard Zebra Optimization Algorithm ZOA. …”
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Collaborative Optimization on Both Weight and Fatigue Life of Fifth Wheel Based on Hybrid Random Forest with Improved BP Algorithm by Huan Xue, Chang Guo, Xiaojian Peng, Saiqing Xu, Kaixian Li, Jianwen Li

“…We proposed a prediction model combining a random forest algorithm with an optimized back propagation (BP) neural network. …”
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Joint Optimization Method for Preventive Maintenance and Train Scheduling of Subway Vehicles Based on a Spatiotemporal Network Graph by Chuanzhen Liu, Zhongwei Xu, Meng Mei, Wenqing Li

“…Finally, an improved genetic algorithm is employed to solve the model and determine the optimal scheduling and maintenance strategy. …”
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Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization by Jomana Yousef Khaseeb, Arabi Keshk, Anas Youssef

“…Three improved binary Grey Wolf Optimization (GWO) approaches are proposed in this paper to optimize the feature selection process by enhancing the feature selection accuracy while selecting the least possible number of features. …”
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Improved ant colony algorithm based cloud computing user task scheduling algorithm by Sining LUO, Hualong WANG, Hongyu LI, Wei PENG

“…In recent years,with the development of power information,more and more power applications and tasks are deployed in the cloud.Because of the dynamic heterogeneity of cloud resources and power applications,it is a challenge in the cloud computing system to realize resource division and task scheduling.Power applications need to be able to achieve a rapid response and minimum completion time,and schedulers should consider the load of each cloud computing node to ensure the reliability of cloud computing.A task scheduling algorithm based on the algorithm of improving an ant colony was proposed to solve the problem of task scheduling in virtual machines.Through the improvement of the standard ant colony algorithm,the task scheduling time was reduced and load balancing was realized while minimizing the overall completion time.The results show that the algorithm can shorten the task scheduling time and realize the load balancing of cloud nodes,which provides technical basis for the optimization of power cloud computing.…”
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Enhanced futures price-spread forecasting based on an attention-driven optimized LSTM network: integrating an improved grey wolf optimizer algorithm for enhanced accuracy by Yongli Tang, Zhenlun Gao, Zhongqi Cai, Jinxia Yu, Panke Qin

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Attack resilient IoT security framework using multi head attention based representation learning with improved white shark optimization algorithm by Jawhara Aljabri

“…This paper presents a multi-head attention-driven intrusion detection with improved white shark optimization algorithm (MHAID-IWSOA) methodology in IoT networks. …”
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FHQ-RRT*: An Improved Path Planning Algorithm for Mobile Robots to Acquire High-Quality Paths Faster by Xingxiang Dong, Yujun Wang, Can Fang, Kemeng Ran, Guohui Liu

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3D Deployment Optimization of Wireless Sensor Networks for Heterogeneous Functional Nodes by Zean Lu, Chengqun Wang, Peng Wang, Weiqiang Xu

“…To address this, an improved Secretary Bird Optimization Algorithm (ISBOA) is proposed, incorporating Gaussian Cuckoo Mutation and a smooth exploitation mechanism. …”
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Ship path planning based on improved multi-scale A* algorithm of collision risk function by Chunyu Song, Teer Guo, Jianghua Sui

“…Moreover, in order to improve the efficiency of optimal path planning in the context of complex sea areas while ensuring path safety, the paper proposes a collision risk function to optimize the determination of the cost of A* algorithm nodes, thereby enhancing the heuristic function of the A* algorithm. …”
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Multi-objective coordinated control and optimization for photovoltaic microgrid scheduling by Da Yu, Kai Hou, Xu Lin, Guoyang Cai, Xin Shan, Weihua Wang

“…This paper proposes a multi-objective coordinated control and optimization system for PV microgrids. To address the challenges of slow convergence and local optima in traditional PV microgrid scheduling methods, this study introduced an improved multiple objective particle swarm optimization (IMOPSO) algorithm that integrates an adaptive inertia weight adjustment strategy based on optimal similarity and a multi-directional iterative Pareto solution archive update mechanism. …”
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The Path Planning of Mobile Robots Based on an Improved Genetic Algorithm by Zheng Zhang, Haobo Yang, Xusheng Bai, Shuo Zhang, Chaobin Xu

“…Bezier curve optimization of the optimal path was conducted. Experimental results show that the improved genetic algorithm demonstrates significant advantages in terms of path length, smoothness, iteration speed, and computational efficiency.…”
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