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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Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe, Reena Jangid

“…The PLO algorithm generates SSE results of 0.025493 for BCS 500 W and 0.275211 for Nedstack 600 W PS6 and 0.283774 for STD 250 W Stack while keeping AE at 0.259293 and RE% at 1.185075 for the STD 250 W Stack. …”
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High-Precision Optimization of BIM-3D GIS Models for Digital Twins: A Case Study of Santun River Basin by Zhengbing Yang, Mahemujiang Aihemaiti, Beilikezi Abudureheman, Hongfei Tao

“…Applied to the Santun River Basin digital twin project, experiments with 10 water gate models show that the AW-QEM algorithm reduces average loading time by 15% compared to traditional QEM, while maintaining 97% geometric accuracy, demonstrating the method’s efficiency in balancing precision and rendering performance.…”
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Optimization of the Mechanical Property of Friction Stir Welded Heat Treatable Aluminum Alloy by using Bio-Inspired Artificial Intelligence Algorithms by Akshansh Mishra, Anish Dasgupta

“…The main objective of the work is to obtain the maximum optimized Ultimate Tensile Strength (MPa) by using Bio-Inspired Artificial Intelligence Algorithms i.e., Differential Evolution and Max Lipschitz optimization (Max LIPO) Algorithm. …”
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Optimization of the Mechanical Property of Friction Stir Welded Heat Treatable Aluminum Alloy by using Bio-Inspired Artificial Intelligence Algorithms by Akshansh Mishra, Anish Dasgupta

“…The main objective of the work is to obtain the maximum optimized Ultimate Tensile Strength (MPa) by using Bio-Inspired Artificial Intelligence Algorithms i.e., Differential Evolution and Max Lipschitz optimization (Max LIPO) Algorithm. …”
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A Comparative Analysis of Advanced Routing and Cluster Head Selection Algorithm Using Lagrange Interpolation by Zoren P. Mabunga, Jennifer C. Dela Cruz, Renato R. Maaliw

“…This paper presents a unified performance metric for evaluating the chronological wild geese optimization (CWGO) algorithm in wireless sensor networks (WSNs). …”
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Remaining Useful Life Prediction of Aero-Engine Based on Improved GWO and 1DCNN by Lihua Shen, Yucheng Wang, Baorui Du, Hailong Yang, He Fan

“…With the deepening adoption of whole-lifecycle management paradigms in aviation equipment, accurate prediction of remaining useful life has emerged as a pivotal technical enabler for ensuring flight safety and optimizing maintenance resource allocation. …”
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Optimizing wireless sensor network topology with node load consideration by Ruizhi Chen

“…The K-means clustering algorithm partitions nodes by minimizing the within-cluster variance, while the firefly algorithm is an optimization algorithm based on swarm intelligence that simulates the flashing interaction between fireflies to guide the search process. …”
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Optimal Capacity Configuration and Day-Ahead Scheduling of Wind-Solar-Hydrogen Coupled Power Generation System by Chengzhen JIA, Lingmei WANG, Enlong MENG, Derong YANG, Dongjie GUO, Yushan LIU

“…In order to realize the optimal capacity allocation and day-ahead scheduling in wind-solar-hydrogen coupled generation system, the NSGA-II intelligent optimization algorithm is used to solve the multi-objective optimization problem of capacity allocation, and the optimal dispatching algorithm considering hydrogen transportation constraint is constructed on power generation side. …”
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Multi-UAV Trajectory Optimization Under Dynamic Threats: An Enhanced GWO Algorithm Integrating a Priori and Real-Time Data by Zihan Zhou, Yanhong Guo, Yitao Wang, Jingfan Lyu, Haoran Gong, Xin Ye, Yachao Li

“…To address this, an enhanced Grey Wolf Optimization (GWO) algorithm is proposed for multi-UAV collaborative planning in dynamic threat zones. …”
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Estimating elastic properties of sediments by pseudo-wells generation utilizing simulated annealing optimization method by Nasser Keshavarz Faraj Khah, Bahare Salehi, Pooria Kianoush, Shahab Varkouhi

“…In this study, the SEAM earth model has been used as a reference to investigate the quality of pseudo-well generation utilizing a simulated annealing (SA) algorithm as an optimization method of property model change, which minimizes the cost function of seismic inversion. …”
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UAV Path Optimization for WSN in Smart Agriculture by Katia Karam, Ali Mansour, Mohamad Khaldi, Benoit Clement, Mohammad Ammad-Uddin

“…The algorithm ensures that the UAV hovers at an optimal position within each sensor’s coverage area, minimizing unnecessary movements. …”
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Alignment Optimization of Elastically Supported Submarine Propulsion Shafting Based on Dynamic Bearing Load Influence Numbers by Jinlin Liu, Zheng Gu, Junhui He, Shijie Cao

“…Taking the equivalent displacements of the bearings as variables, the alignment optimization of the shafting was achieved by combining the genetic algorithm and the response surfaces. …”
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Edge detection of aerial images using artificial bee colony algorithm by Nurdan Akhan Baykan, Elif Deniz Yelmenoglu

“…In this paper, aerial images are used for edge information extraction by using Artificial Bee Colony (ABC) Optimization Algorithm. Procedures were performed on gray scale aerial images which are taken from RADIUS/DARPA-IU Fort Hood database. …”
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A Chaotic Decomposition-Based Approach for Enhanced Multi-Objective Optimization by Javad Alikhani Koupaei, Mohammad Javad Ebadi

“…The results establish the proposed algorithm as a promising alternative for solving multi-objective optimization problems.…”
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Optimizing quantum convolutional neural network architectures for arbitrary data dimension by Changwon Lee, Israel F. Araujo, Dongha Kim, Junghan Lee, Siheon Park, Ju-Young Ryu, Ju-Young Ryu, Daniel K. Park, Daniel K. Park

“…., the number of features) of the input data that can be processed, restricting the applicability of QCNN algorithms to real-world data. To address this issue, we propose a QCNN architecture capable of handling arbitrary input data dimensions while optimizing the allocation of quantum resources such as ancillary qubits and quantum gates. …”
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MULTI-OBJECTIVE OPTIMIZATION OF A MEDICAL ROBOT MODEL IN TRANSIENT STATES by Grzegorz ILEWICZ, Andrzej HARLECKI

“…In order to uncover the optimal solution, a multi-objective genetic algorithm was used, guaranteeing the optimality of the manipulator model in the Pareto sense. …”
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A multi-objective aerodynamic performance optimization of a centrifugal vacuum pump and the flow physics analysis by Zhanyuan Gu, Jiangtao Zhang, Wei Zhang, Yikun Wei

“…The backpropagation neural network was employed as the surrogate model, and the multi-objective optimization was performed using the non-dominated sorting genetic algorithm. …”
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Optimizing Residential Electricity Demand with Bipartite Models for Enhanced Demand Response by Jonathan Campoverde, Marcelo Garcia Torres, Luis Tipan

“…This study presents an advanced energy demand management approach within residential microgrids using bipartite models for optimal demand response. The methodology relies on linear programming, specifically the Simplex algorithm, to optimize power distribution while minimizing costs. …”
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Multi-objective multi-workflow task offloading based on evolutionary optimization by Teliekebieke Misha, Lisheng Sun, Zheng-yi Chai

“…Simulation results demonstrate that our algorithm optimally balances delay and energy consumption requirements compared to existing methods, while enhancing the diversity and convergence of non-dominated solutions.…”
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