Improving detection of Parkinson’s disease with acoustic feature optimization using particle swarm optimization and machine learning by Elmoundher Hadjaidji, Mohamed Cherif Amara Korba, Khaled Khelil

“…This study aims to refine PD detection systems by introducing customized weighting to acoustic features, adjusting their significance based on their correlation with the disease and the classification algorithm utilized. The particle swarm optimization algorithm is employed for this purpose, with the Oxford PD dataset serving as the source data for training and validation. …”
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Grid-connected PV inverter system control optimization using Grey Wolf optimized PID controller by Monika Gupta, P. M. Tiwari, R. K. Viral, Ashish Shrivastava, Basem Abu Zneid, Iryna Hunko

“…Abstract This paper introduces a robust and adaptive control framework that integrates a Proportional–Integral–Derivative (PID) controller with the bio-inspired Grey Wolf Optimization (GWO) algorithm for real-time tuning of controller parameters in grid-connected photovoltaic (PV) inverter systems. …”
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Fuzzy Optimized Attention Network with Multi-Instance Deep Learning (FOAN-MIDL) for Alzheimer’s Disease Diagnosis with Structural Magnetic Resonance Imaging (sMRI) by Afnan M. Alhassan, Nouf I. Altmami

“…<b>Results:</b> An attention technique to estimate the weight of every case is presented: the fuzzy salp swarm algorithm (FSSA). The swarming actions of salps in oceans serve as the inspiration for the FSSA. …”
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Modified Swarm-Based Artificial Intelligence Optimization for Optimal Coordination of Directional Overcurrent Relays in Power System by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Herie Park

“…The coordination of directional overcurrent relays (DOCRs) plays a critical role in ensuring the reliability and robustness of modern electrical power protection systems. Achieving optimal relay coordination in multi-loop power networks is a complex optimization challenge requiring the minimization of relay operating times and achieve optimal tuning of time dial settings (TDS) and plug settings (PS) while considering the impact of DG integration. …”
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Research on Multi-Target Point Path Planning Based on APF and Improved Bidirectional RRT* Fusion Algorithm by Zijian Bian, Gang Li, Xizheng Wang

“…A multi-target point heuristic planning strategy is proposed to achieve shorter global paths while maintaining shorter local paths, taking into account both local solutions and optimal solutions, so that the fusion algorithm can be applied to the path planning of multi-target points.…”
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Planning trajectory for UAVs using the self-organizing migrating algorithm. by Quoc Bao Diep, Thanh-Cong Truong, Ivan Zelinka

“…To optimize this cost function, we employ the self-organizing migrating algorithm, a swarm intelligence algorithm inspired by the cooperative and competitive behaviors observed in natural organisms. …”
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An Improved Small Target Detection Algorithm Based on YOLOv8s by G. Ma, C. Xu, Z. Xu, X. Song

“…To address these challenges, this pa¬per proposes an enhanced small object detection algorithm, SOD-YOLO, based on YOLOv8s. First, the S_C2f_CAFM module is integrated into the feature extraction network, enabling the effective capture of fine-grained local features and broad contextual information, while simultaneously reducing model parameters and computational complexity. …”
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Honeyword Generation Using a Proposed Discrete Salp Swarm Algorithm by Yasser A. Yasser, Ahmed T. Sadiq, Wasim AlHamdani

“…This work will present a novel honeyword generation method that uses a proposed discrete salp swarm algorithm. The salp swarm algorithm (SSA) is a bio-inspired metaheuristic optimization algorithm that imitates the swarming behavior of salps in their natural environment. …”
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Development of an Algorithm to Determine the Most Efficient Trajectories in Directional Wells by R.R. Francisco, M. Bertuzzi, G.V.V. Ramlov, L.A. Alves, C.E. Metzler

“…The primary goal is to optimize the trajectory by minimizing the tension and torques applied to the drill column during drilling operations while ensuring the well stability and operational efficiency. …”
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Overcoming Data Scarcity in Calibrating SUMO Scenarios With Evolutionary Algorithms by Jakob Kappenberger, Heiner Stuckenschmidt

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MGL-YOLO: A Lightweight Barcode Target Detection Algorithm by Yuanhao Qu, Fengshou Zhang

“…Experimental results show that the proposed algorithm increases MAP50 and MAP50.95 by 2.57% and 2.31%, respectively, compared to YOLOv8, while reducing parameter size and computational cost by 36.21% and 34.15%, respectively. …”
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Classification of Internet banking customers using data mining algorithms by Reza Radfar, Navid Nezafati, Saeid Yousefi Asli

“…Classifying customers using data mining algorithms, enables banks to keep old customers loyality while attracting new ones. …”
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Unraveling regional variability in Dengue outbreaks in Brazil: leveraging the Moving Epidemics Method (MEM) and climate data to optimize vector control strategies. by Ayrton Sena Gouveia, Marcelo Ferreira da Costa Gomes, Iasmim Ferreira de Almeida, Raquel Martins Lana, Leonardo Soares Bastos, Lucas Monteiro Bianchi, Sara de Souza Oliveira, Eduardo Correa Araujo, Danielle Andreza da Cruz Ferreira, Dalila Machado Botelho Oliveira, Vinicius Barbosa Godinho, Luã Bida Vacaro, Thais Irene Souza Riback, Oswaldo Gonçalves Cruz, Flávio Codeço Coelho, Cláudia Torres Codeço

“…A multivariate cluster analysis using the k-means algorithm was applied to MEM outputs and climate data. …”
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UAV Signal Modulation Recognition Algorithm Based on Joint Features by Yang Zheng, Zhihai Zhuo

“…After quantization, the recognition performance remains nearly unaffected, while computational resource requirements are greatly reduced, making the algorithm highly suitable for deployment in resource-constrained environments.…”
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Trajectory Similarity Algorithm Based on DTW and Trajectory Point Compression by GAO Wei, QIAN Chengyang, ZHANG Qi, XIE Hongquan

“…Understanding the behavior characteristics of these holders through processing massive trajectory data has become an important issue to be addressed using trajectory similarity algorithms. To optimize the computational efficiency of the algorithm while maintaining its accuracy, this paper presents an algorithm based on an improved dynamic time warping (DTW) algorithm, i.e. the compression DTW (CN-DTW) algorithm to overcome the deficiencies of long running time and ill-conditioned alignment in the DTW algorithm. …”
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Optimizing Investment Portfolios with Bacterial Foraging and Robust Risk Management by Hubert Zarzycki

“…BFO, a nature-inspired algorithm, is employed to construct diversified portfolios, while risk management strategies, including stop-loss limits and transaction cost considerations, enhance risk control. …”
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Dynamically optimal models of atmospheric motion by A. G. Voronovich

“…</p></li><li> <p id="d2e91">The spatial resolution can be adjusted locally while executing calculations.</p></li><li> <p id="d2e95">By using a set of tetrahedra as finite elements the algorithm ensures a better representation of the topography (piecewise linear rather than staircase).…”
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Application of the Random Forest Algorithm for Accurate Bipolar Disorder Classification by Miguel Suárez, Ana M. Torres, Pilar Blasco-Segura, Jorge Mateo

“…These results highlight the algorithm’s capacity to handle complex, noisy datasets while identifying key features relevant for classification. …”
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MODELING AND OPTIMIZATION OF VEHICLE SUSPENSION OSCILLATIONS by N. N. Hurski, A. Kader Karami

“…Results on optimization of suspension oscillations by minimum vibro-acceleration  of cushioned mass while a vehicle is moving within the preset speed interval are presented in the paper.…”
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Lightweight insulator target detection algorithm based on improved YOLOX by Bing Zeng, Wei Hua, Dezhi Li, Zhihao Zhou, Hao Wan, Yunmin Xie, Tangbing Li, Yucong Chen, Jianglei Li, Shenli Wang, Shixun Fu, Zihan Jin, Wenhua Zhang

“…Finally, the σWIoU loss function replaces the traditional IoU to accelerate convergence and optimize overall performance. Experiments show that compared to the original YOLOX, the proposed algorithm reduces parameters by 53.41% to 4.164 M and computational load to 12.975G, with mAP increased by 1.3%, detection accuracy reaching 98.81%, and recall achieving 100%. …”
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