Exploration and comparison of the effectiveness of swarm intelligence algorithm in early identification of cardiovascular disease by Tiantian Bai, Mengru Xu, Taotao Zhang, Xianjie Jia, Fuzhi Wang, Xiuling Jiang, Xing Wei

“…Subsequently, the selected feature subsets were integrated into ten classification models, and a comprehensive weighted evaluation was performed based on the accuracy, precision, recall, F1 score, and AUC value of the model to determine the optimal model configuration. The results showed that random forest, extreme gradient boosting, adaptive boosting and k-nearest neighbor models performed best on the combined dataset (weighted score of 1), where the feature set consisted of 9 key features selected by the cuckoo search algorithm when the population size was 25; while on the Framingham dataset, the k-nearest neighbor model performed best (weighted score of 0.92), and its feature set was derived from 10 features selected by the whale optimization algorithm when the population size was 50. …”
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Optimization of Fusion Method for GF-2 Satellite Remote Sensing Images based on the Classification Effect by Jintong Ren, Wunian Yang, Xin Yang, Xiaoyu Deng, He Zhao, Fang Wang, Lei Wang

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Multi-objective optimization and parameter sensitivity study on microreactor nuclear power systems by Ersheng You, Yiyi Li, Jianjun Xu, Dianchuan Xing, Haochun Zhang

“…The PSO algorithm code was used to calculate and compare the benchmark case of MRNPS, and the optimized Pareto optimal solution set was obtained. …”
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A Ultra-Low Cost and Accurate AMC Algorithm and Its Hardware Implementation by Yuqin Zhao, Tiantai Deng, Bill Gavin, Edward A. Ball, Luke Seed

“…In this design, the CAMC algorithm is optimized to fit the FPGA characteristics to further improve the performance, and the computing demands of which could be saved over 94% compared with other state-of-the-art designs. …”
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A Comparison of Heuristic Algorithms for Solving the Traveling Salesman Problem by Younes Khdeir, Ahmed Awad

“…The study examines how these algorithms can solve the TSP and avoid local minimum values while achieving a balance between research exploration and exploitation for an optimal solution. …”
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Enhanced energy-efficient cluster-based routing with spotted hyena optimization in heterogeneous WSNs by Ved Prakash, Suman Pandey, Biswa Mohan Sahoo

“…Abstract Wireless sensor networks (WSNs) are crucial in many applications; hence, it is important to have routing algorithms that are energy-efficient in order to extend the lifespan of the network. …”
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A new smart charging electric vehicle and optimal DG placement in active distribution networks with optimal operation of batteries by Bilal Naji Alhasnawi, Marek Zanker, Vladimír Bureš

“…Thirdly, this paper proposes an optimization technique based on the Mountain Gazelle Optimizer (MGO), Improved Beluga Whale Optimization (IBWO), and Arithmetic Optimization Algorithm (AOA) for determining the optimal DGs in radial distribution systems. …”
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Adaptive Sharding for UAV Networks: A Deep Reinforcement Learning Approach to Blockchain Optimization by Kaiyin Lu, Xinguang Zhang, Tianbo Zhai, Mengjie Zhou

“…The proposed optimizations focus on dual objectives: enhancing data security while concurrently accelerating processing speeds. …”
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Flexible Reconfiguration for Optimal Operation of Distribution Network Under Renewable Generation and Load Uncertainty by Behzad Esmaeilnezhad, Hossein Amini, Reza Noroozian, Saeid Jalilzadeh

“…The uncertainty of the load and generation from renewable energies is planned to use their probability density functions via a scenario-based approach. The suggested optimization problem is solved using a metaheuristic approach based on the coati optimization algorithm (COA) due to the nonlinearity and non-convexity of the problem. …”
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Advancing Multi-UAV Inspection Dispatch Based on Bilevel Optimization and GA-NSGA-II by Yujing Liu, Chunmei Chen, Yu Sun, Shaojie Miao

“…In multi-UAV collaborative power grid inspection, the system efficiency of existing methods is limited by the performance of both task assignment and path planning, which is critical in large-scale task scenarios, resulting in a huge computational cost and a high possibility to local optimality. To address these challenges, a bilevel optimization framework based on GA-NSGA-II and task segmentation is proposed to balance the total inspection distance and the distance standard deviation of UAVs, where the outer optimization employs the NSGA-II to assign task units to each UAV evenly, while the inner optimization deploys an adaptive genetic algorithm with an elite retention strategy to optimize the inspection direction and order in each task domain to obtain a Pareto-optimal solution set under constraints. …”
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Optimization of Sensor Positions and Orientations for Multiple Load Case Scenarios by Wacław Kuś, Waldemar Mucha, Iyasu Tafese Jiregna

“…This paper focuses on optimizing sensor placement in structures for load monitoring applications. …”
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Research on Mobile Robot Path Planning Based on MSIAR-GWO Algorithm by Danfeng Chen, Junlang Liu, Tengyun Li, Jun He, Yong Chen, Wenbo Zhu

“…Finally, the elimination and relocation strategy based on stochastic center-of-gravity dynamic reverse learning is introduced for the inferior individuals in the population, which effectively maintains the diversity of the population and improves the convergence speed of the algorithm while avoiding falling into the local optimal solution effectively. …”
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EEG channels selection for stroke patients rehabilitation using equilibrium optimizer by Al-Betar Mohammed Azmi, Alyasseri Zaid Abdi Alkareem, Makhadmeh Sharif Naser

“…This article addresses this problem by presenting an innovative optimization-based approach to the channel selection problem, employing a novel binary equilibrium optimizer (EO) as an optimization technique to identify the most relevant EEG channels. …”
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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…In addition, the second phase is named feature selection, and it is dependent on the Arithmetic Optimization Algorithm (AOA) being used to improve the Growth Optimizer (GO). …”
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Enhanced COVID-19 Optimization Algorithm for Solving Multi-Objective Optimal Power Flow Problems with Uncertain Renewable Energy Sources: A Case Study of the Iraqi High-Voltage Gri... by Basim ALBaaj, Orhan Kaplan

“…Various optimization algorithms have been developed to address this issue. …”
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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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Optimal Power Management to Minimize SER in Amplify and-Forward Relay Networks by M. Abedi, M. J Emadi

“…For this scenario, the maximum SER is minimized over the whole harvesting time slots. We propose a water filling algorithm for the classical relay channel and an iterative algorithm for the multi-branch single-relay cooperative scheme. …”
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A Methodology to Characterize an Optimal Robotic Manipulator Using PSO and ML Algorithms for Selective and Site-Specific Spraying Tasks in Vineyards by Roni Azriel, Oded Degani, Avital Bechar

“…It compares the current approach for optimizing manipulator configurations, which relies on simulation and optimization algorithms, with an improved methodology that integrates machine learning models to enhance the optimization process. …”
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Enhanced Design of a Hand Exoskeleton: Balancing Force Transmission and Actuation With Evolutionary Algorithms by Baris Akbas, Huseyin Taner Yuksel, Aleyna Soylemez, Mine Sarac, Fabio Stroppa

“…The optimization relies on a Genetic Algorithm, the Big Bang-Big Crunch Algorithm, and their versions for multi-objective optimization. …”
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Optimizing Vehicle Body Cross-Sections Using a Parametric Mathematical Model by Zhaohui Hu, Shuai Mo, Huang Liu, Fuhao Mo

“…Then, the stochastic gradient genetic algorithm is used to optimize the solution and determine the geometric parameters of each section. …”
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