Automated Calibration of SWMM for Improved Stormwater Model Development and Application by Hossein Ahmadi, Durelle Scott, David J. Sample, Mina Shahed Behrouz

“…During multi-objective optimization calibration, the model achieved NSE, PBIAS, and RSR values of 0.73, 17.1, and 0.52, respectively; while the validation period recorded values of 0.86, 13.1, and 0.37, respectively. …”
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Marine fish species recognition based on improved YOLOv5s by ZHANG Haifeng, LU Xinchun, FENG Bo, YANG Jin

“…ObjectiveIn order to improve the recognition accuracy of different kinds of marine fish, an improved YOLOv5s marine fish species recognition method was proposed.MethodsK⁃means++algorithm was used to cluster the real frames of marine fish, and more matching anchor frames were obtained with the self built data set. …”
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The WSN Localization Algorithm Integrating Ranging Correction and Spider Wasp Optimization by YU Xiu-wu, XIAO Lin, LIU Yong, YE Lai

“…The objective is to improve the accuracy of node localization and enhance the overall performance of the DV-Hop algorithm, making it more reliable in practical deployment scenarios.MethodsThe proposed algorithm consists of two main components: distance correction and optimization using Spider Wasp Optimization (SWO). …”
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EG-DPoS: Optimized DPoS Consensus Algorithm Based on Evolutionary Game by LIU Yong, DENG Xiaohong, LIU Lihui, SHI Yiran, ZHANG Li

“…The proportional coefficient of credit value and voting weight in the process of agent node election is balanced to reduce the oligopoly phenomenon caused by nodes with high credit value, while the roulette selection algorithm is used to randomize the block generation order of agent nodes, to avoid nodes being attacked during block generation and improve the security of the system. …”
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YOLO-WWBi: An Optimized YOLO11 Algorithm for PCB Defect Detection by Yi Zhao, Zhidi Jiang

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Distributed K-Means algorithm based on a Spark optimization sample. by Yongan Feng, Jiapeng Zou, Wanjun Liu, Fu Lv

“…To address the instability and performance issues of the classical K-Means algorithm when dealing with massive datasets, we propose SOSK-Means, an improved K-Means algorithm based on Spark optimization. …”
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Investigation of a Multi-Strategy Ensemble Social Group Optimization Algorithm for the Optimization of Energy Management in Electric Vehicles by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…A multi-strategy ensemble social group optimization algorithm (ME-SGO) to improve the exploration for complex and composite landscapes through distance-based strategy adaption and success-based parameter adaption while incorporating linear population reduction is proposed. …”
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Optimal performance design of bat algorithm: An adaptive multi‐stage structure by Helong Yu, Jiuman Song, Chengcheng Chen, Ali Asghar Heidari, Yuntao Ma, Huiling Chen, Yudong Zhang

“…Abstract The bat algorithm (BA) is a metaheuristic algorithm for global optimisation that simulates the echolocation behaviour of bats with varying pulse rates of emission and loudness, which can be used to find the globally optimal solutions for various optimisation problems. …”
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Application of Blocplan and Aldep Algorithms for Optimizing Production Layout at Meatball Factory by Thabed Tholib Baladraf

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A Group Search Algorithm for Optimal Scheduling of Cascade Hydropower Stations by WANG Kechao, CAI Ruoyi, SHEN Jianjian

“…The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to address the optimal scheduling problem of cascade hydropower plants, and an improved algorithm called LCHIO was proposed. …”
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A Group Search Algorithm for Optimal Scheduling of Cascade Hydropower Stations by WANG Kechao, CAI Ruoyi, SHEN Jianjian

“…The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to address the optimal scheduling problem of cascade hydropower plants, and an improved algorithm called LCHIO was proposed. …”
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Exploring Evolutionary Algorithms for Multi-Objective Optimization in Seismic Structural Design by Seda Göktepe Körpeoğlu, Süleyman Mesut Yılmaz

“…While genetic algorithms are used to improve both the cost and seismic performance of the structure, particle swarm optimization is used to optimize the vibration and displacement performance of structures. …”
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Hybrid strategy enhanced crayfish optimization algorithm for breast cancer prediction by Yu-Jiong Li

“…When combined with Extreme Learning Machine (ELM) and applied to the Wisconsin breast cancer dataset, the MSCOA-ELM model achieved 100% accuracy and F1 score, a 28.9% improvement over the baseline ELM, demonstrating the algorithm’s efficiency and generalization ability in solving practical optimization problems.…”
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PID CONTROLLER FOR SPEED CONTROL OF PMSM BASED ON MAYFLY OPTIMIZATION ALGORITHM by Fatimah F. Jaber

“…Nuptial dancing and random flight improve the ability of the algorithm to balance its features of exploitation and exploration while assisting in its escape from local optima. …”
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Genetic Algorithm for Optimal Control Design to Gust Response for Elastic Aircraft by Mauro Iavarone, Umberto Papa, Alberto Chiesa, Luca de Pasquale, Angelo Lerro

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Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization by Fan Zhang, Chuankai Liu, Peng Liu, Shuiting Ding, Tian Qiu, Jiajun Wang, Huipeng Du

“…Abstract This study proposes BAGWO, a novel hybrid optimization algorithm that integrates the Beetle Antennae Search algorithm (BAS) and the Grey Wolf Optimizer (GWO) to leverage their complementary strengths while enhancing their original strategies. …”
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Optimizing energy constrained target localization and tracking with radial bias and seeker optimization algorithms in wireless sensor networks by S. Yazhinian, S. Famila, P. Jose, Mahendar A, Sofia R

“…It is seen that the proposed RadB_SOA achieves 12.4 % of transmission error, 14.6 % of ranging error, 96.3 % of localization coverage, 98.65 % of PDR, and 21.56 % of energy consumption. • The Radial Bias-Seeker Optimization Algorithm (RadB_SOA) suggested enhances the precision in target localization and optimizes energy usage in wireless sensor networks. • Simulation outcomes reveal improved tracking accuracy, minimized transmission and ranging errors, as well as increased localization coverage over current techniques. • The research presents an extensive evaluation of particle count fluctuations in RBSO, demonstrating enhanced positioning speed and precision with network efficiency.…”
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Resource optimization algorithm of combination of NFV and SDN for application of multiple services by Xiaorong ZHU, Qian ZHANG

“…Various services of internet of things (IoT) require flexible network deployment to guarantee different quality of service (QoS).Aiming at the problem of IoT service function chain deployment,network function virtualization (NFV) and software defined networking (SDN) were combined to optimize resources.Considering forwarding cost and traffic load balance,a joint optimization model of virtual network function placement and service function chain routing was given and was proved to be NP-Hard.In order to solve this model,two heuristic algorithms were proposed.One was the service chain deployment algorithm of first routing then placing (FRTP) and the other was the placing followed by routing (PFBR) based on node priority.Simulation results demonstrate that FRTP and PFBR algorithm can significantly balance network traffic load while alleviating congestion and improving the acceptance ratio of the chain requests compared with other algorithms.…”
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Research on Algorithms for Local Robot Positioning Using Methods of Discrete Optimization by Vyacheslav Korolyov, Maksim Ogurtsov, Oleksandr Khodzinskyi

“…By anchoring one object to the origin point and fixing the position of the second object on the horizontal axis, the problem of ambiguity in the solution, manifested in the symmetrical reflection of points and their displacement relative to real positions, has been resolved. Conclusions. Improvements to the existing local positioning system robot group based on an enhanced discreet optimization algorithm are discussed. …”
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CSA: Utility Optimization Scheduling Algorithm for IoT Blockchain Sharding Committees by Xin Cong, Qi Jing, Lingling Zi, Changjiang Lin

“…CSA dynamically adjusts the committee members to achieve near-optimal solutions while addressing operational constraints. …”
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