Challenges and Opportunities for Applying Meta-Heuristic Methods in Vehicle Routing Problems: A Review by Wayan Firdaus Mahmudy, Agus Wahyu Widodo, Alfabiet Husien Haikal

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A novel TID + IDN controller tuned with coatis optimization algorithm under deregulated hybrid power system by Geetanjali Dei, Deepak Kumar Gupta, Binod Kumar Sahu, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

Subjects: “…Improved squirrel search algorithm (ISSA)…”
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Dynamic neutrosophic cognitive map with improved cuckoo search algorithm (DNCM-ICSA) and ensemble classifier for rheumatoid arthritis (RA) disease by B. Chithra, R. Nedunchezhian

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Guided Particle Swarm Optimization for Feature Selection: Application to Cancer Genome Data by Simone A. Ludwig

“…This paper presents a feature selection method based on Particle Swarm Optimization (PSO). The proposed algorithm makes use of a guided particle scheme whereby three filter-based methods are incorporated. …”
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MHD Free Convection in an Enclosure Loaded with Nanofluid and Partially Cross-heated by A. Marfouk, A. Mansour, A. Hasnaoui, A. Amahmid, M. Hasnaoui

“…The influence of Brownian motion and thermophoresis on particle motion through the Buongiorno model is reviewed. …”
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MSCSO: A Modified Sand Cat Swarm Algorithm for 3D UAV Path Planning in Complex Environments with Multiple Threats by Zhengsheng Zhan, Dangyue Lai, Canjian Huang, Zhixiang Zhang, Yongle Deng, Jian Yang

“…To improve the global search efficiency and dynamic adaptability of the Sand Cat Swarm Optimization (SCSO) algorithm for UAV path planning in complex 3D environments, this study proposes a Modified Sand Cat Swarm Optimization (MSCSO) algorithm by integrating chaotic mapping initialization, Lévy flight–Metropolis hybrid exploration mechanisms, simulated annealing–particle swarm hybrid exploitation strategies, and elite mutation techniques. …”
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Spurious-Free Dynamic Range Augmentation for Digital-to-Analog Converters using PSO-PID Adaptive Algorithms by Junshi Lv, Chengting Zhang, Honglv Wang, Gaoming Xu, Taijun Liu

“…In this paper, we propose a new method for enhancing the spurious-free dynamic range (SFDR) of digital-to-analog converters (DACs) by implementing a digital predistorter to suppress harmonic distortion. First, the particle swarm optimization (PSO) algorithm is used to optimize the proportional-integral-derivative (PID) parameters, after which the PSO-PID algorithm is implemented to identify the best signal featuring the least harmonic distortion. …”
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Demand Prediction of Emergency Supplies under Fuzzy and Missing Partial Data by Ming Zhang, Hanlin Wu, Zhifeng Qiu, Yifan Zhang, Boquan Li

“…This study aims at improving supplies demand prediction accuracy under partial data fuzziness and missing. The main contributions of this study are summarized as follows. (1) In view that it is difficult for the turning point of the whitenization weight function to determine fuzzy data, two computational formulas solving “core” of fuzzy interval grey numbers were proposed, and the obtained “core” replaced primary fuzzy information so as to reach the goal of transforming uncertain information into certain information. (2) For partial data missing, the improved grey k-nearest neighbor (GKNN) algorithm was put forward based on grey relation degree and K-nearest neighbor (KNN) algorithm. …”
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Partial discharge pattern recognition based on EEMD singular value entropy by Luo Riping, Luo Yingting, Lai Shiyu, Zhao Xianyang, Wang Liqi

“…Secondly, the singular value decomposition is performed on the reconstructed signal, and the singular value entropy is calculated in combination with the information entropy algorithm. Finally, according to the singular value entropy, the type of GIS partial discharge is distinguished. …”
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Bayesian Adaptive Lasso for the Partial Functional Linear Spatial Autoregressive Model by Dengke Xu, Ruiqin Tian, Ying Lu

“…This study introduces a partial functional linear spatial autoregressive model which can explore the relationship between a scalar spatially dependent response variable and predictive variables containing both multiple scalar covariates and a functional covariate. …”
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Equilibrium Strategies for Overtaking-Free Queueing Networks under Partial Information by David Barbato, Alberto Cesaro, Bernardo D’Auria

“…We investigate the equilibrium strategies for customers arriving at overtaking-free queueing networks and receiving partial information about the system’s state. In an overtaking-free network, customers cannot be overtaken by others arriving after them. …”
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GIS partial discharge fault diagnosis method based on SGMD-LSTM by Zhang Yun, Zhang Chao, Zhang Shiyong, Ma Pengchi, Yang Guang, Ding Hao

“…To accurately diagnose partial discharge faults in Gas Insulated Switchgear (GIS), a fault diagnosis method based on Symplectic Geometric Mode Decomposition (SGMD) and improved Long Short Term Memory (LSTM) is proposed. …”
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On the Partial Offloading to Multiple Helpers-Based Task Offloading for IoT Networks by Usman Mahmood Malik, Muhammad Awais Javed, Abdulaziz AlMohimeed, Mohammed Alkhathami, Abeer Almujalli

“…We propose a modified many-to-many matching-based task offloading algorithm to reduce the task latency in a POMH scenario. …”
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Using UMAP for Partially Synthetic Healthcare Tabular Data Generation and Validation by Carla Lázaro, Cecilio Angulo

“…In addition, the common case of lack of information due to technical issues, transcript errors, or differences between descriptors considered in different health centers leads to the need for data imputation and partial data generation techniques. This study introduces a novel methodology for partially synthetic tabular data generation, designed to reduce the reliance on sensor measurements and ensure secure data exchange. …”
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Research on Model Reconstruction Methods for Partial Point Cloud Information Loss by Zhengping CHANG, Guoshuai YUAN, Jiuhua LI, Yang ZHAO, Zhongqi WANG

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Convergence-Driven Adaptive Many-Objective Particle Swarm Optimization by Yunfei Yi, ZhiYong Wang, Yunying Shi, Zhengzhuo Song, Binbin Zhao

“…To overcome these challenges, this study proposes a Convergence-Driven Adaptive Many-Objective Particle Swarm Optimization (CDA-MOPSO) algorithm. …”
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The Design of Contactors Based on the Niching Multiobjective Particle Swarm Optimization by Wenying Yang, Jiuwei Guo, Yang Liu, Guofu Zhai

“…To avoid missing the extreme solutions of each objective during the multiobjective optimization process, extra particle swarms used to search the independent optimal solution of each objective are supplemented in this algorithm. …”
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Constrained Fuzzy Predictive Control Using Particle Swarm Optimization by Oussama Ait Sahed, Kamel Kara, Mohamed Laid Hadjili

“…This can be achieved using reduced population size and small number of iterations. In this algorithm, instead of using the uniform distribution as in the conventional PSO algorithm, the initial particles positions are distributed according to the normal distribution law, within the area around the best position. …”
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Filter Learning-Based Partial Least Squares Regression and Its Application in Infrared Spectral Analysis by Yi Mou, Long Zhou, Weizhen Chen, Jianguo Liu, Teng Li

“…Partial Least Squares (PLS) regression has been widely used to model the relationship between predictors and responses. …”
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Offline Magnetometer Calibration Using Enhanced Particle Swarm Optimization by Lei Huang, Zhihui Chen, Jun Guan, Jian Huang, Wenjun Yi

“…To address the decline in measurement accuracy of magnetometers due to process errors and environmental interference, as well as the insufficient robustness of traditional calibration algorithms under strong interference conditions, this paper proposes an ellipsoid fitting algorithm based on Dynamic Adaptive Elite Particle Swarm Optimization (DAEPSO). …”
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