Formulation of multicriteria problem of routing and scheduling of manned and unmanned aircraft in a dynamic environment and approach to its solution using genetic algorithms by G. N. Lebedev, V. B. Malygin, D. A. Mikhaylin, T. Byo

“…A mathematical statement of the problem is formulated and a universal optimality criterion is proposed in the form of a sum of additive and multiplicative forms, including partial quality indicators. The search for optimal and rational solutions to the problem of optimal flight routing, taking into account the airline fleet resources, airspace users' offers, constant and variable restrictions, associated, for example, with unfavorable weather conditions, can be implemented using a one-criteria and multi-criteria approach, but as a result, it is proposed to use a genetic algorithm that has low computational complexity and offers as solutions ("ancestors"), close to the optimal and rational result.  …”
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Evolutionary Cost Analysis and Computational Intelligence for Energy Efficiency in Internet of Things-Enabled Smart Cities: Multi-Sensor Data Fusion and Resilience to Link and Devi... by Khalid A. Darabkh, Muna Al-Akhras

“…When compared to the most recent and relevant protocols, including the Particle Swarm Optimization-based energy-efficient clustering protocol (PSO-EEC), linearly decreasing inertia weight PSO (LDIWPSO), Optimized Fuzzy Clustering Algorithm (OFCA), and Novel PSO-based Protocol (NPSOP), our approach achieves very promising results. …”
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Remote sensing estimation of chlorophyll content in rape leaves in Weibei dryland region of China by Xia Liheng, Zhang Panpan, Shi Lei, Wang Kun, Zhang Tingyu

“…Subsequently, single-factor models, partial least squares regression models, Back Propagation neural network (BPNN) models, Genetic Algorithm (GA) optimization BPNNs, and BPNN models optimized through GAs based on multiple linear stepwise regression using spectral parameters (referred to as MLSR-GA-BP NN models) were constructed and compared. …”
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Optimizing LoRaWAN Gateway Placement in Urban Environments: A Hybrid PSO-DE Algorithm Validated via HTZ Simulations by Kanar Alaa Al-Sammak, Sama Hussein Al-Gburi, Ion Marghescu, Ana-Maria Claudia Drăgulinescu, Cristina Marghescu, Alexandru Martian, Nayef A. M. Alduais, Nawar Alaa Hussein Al-Sammak

“…This study investigates how to optimize the placement of LoRaWAN gateways by using a combination of Particle Swarm Optimization (PSO) and Differential Evolution (DE). …”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
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Redefining Trauma Triage for Elderly Adults: Development of Age-Specific Guidelines for Improved Patient Outcomes Based on a Machine-Learning Algorithm by Ji Yeon Lim, Yongho Jee, Seong Gyu Choi, Yoon Hee Choi, Sam S. Torbati, Carl T. Berdahl, Sun Hwa Lee

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Production and optimization of affordable artificial geopolymer aggregates containing crumb rubber, plastic waste, and granulated cork based on machine learning algorithms by Mohamed Abdellatief, Abedulgader Baktheer, Mohamed Shahin, Aref A. Abadel, Ashraf M. Heniegal

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The Development and Application of Multi-Cell Elliptical Superconducting Cavity Pre-Tuning Equipment by Ahong Li, Lin Meng, Huachang Liu, Yao Yang, Qiang Chen, Bo Li, Xiaolei Wu, Peihua Qu, Mengxu Fan, Wenzhong Zhou, Cong Zhang

“…Elliptical superconducting cavities are widely used in particle accelerators because they can provide stronger acceleration fields than regular cavities. …”
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Portfolio optimization with MOPSO-Shrinkage hybrid model by Minh Tran, Nhat M. Nguyen

“…This paper introduces a novel framework for portfolio optimization that integrates Multi-Objective Particle Swarm Optimization (MOPSO) with shrinkage covariance estimators, referred to as the MOPSO-Shrinkage hybrid model. …”
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FastSLAM-MO-PSO: A Robust Method for Simultaneous Localization and Mapping in Mobile Robots Navigating Unknown Environments by Xu Bian, Wanqiu Zhao, Ling Tang, Hong Zhao, Xuesong Mei

“…Our empirical evaluation involves testing the proposed method on three distinct simulation benchmarks, comparing its performance against four other algorithms. The results indicate that our MO-PSO-enhanced FastSLAM method outperforms the traditional particle filtering approach by significantly reducing particle degeneration and ensuring more reliable and precise SLAM performance in challenging environments. …”
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Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm by Roozbeh Moazenzadeh, Okan Mert Katipoğlu, Ahmadreza Shateri, Hamid Nasiri, Mohammed Abdallah

“…The superiority of the proposed model (XGB-MPA) compared to two other hybrid models, including XGB-PSO (Particle Swarm Optimization) and XGB-GWO (Grey Wolf Optimization) was also investigated. …”
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Development, optimization and modelling of performance parameters for remote-controlled mechatronic precision planter using RSM and Hybrid PSO-ANN model by Vimalsinh Vala, Rajvir Yadav, Bikram Jyoti, Ali Salem, Ajay K Roul, Rahul Potdar, Ankur Srivastava, Ahmed Elbeltagi

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Paired autoencoders for likelihood-free estimation in inverse problems by Matthias Chung, Emma Hart, Julianne Chung, Bas Peters, Eldad Haber

“…The main computational bottleneck of typical algorithms is the direct estimation of the data misfit. …”
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Hybrid Energy Management of Solid Oxide Fuel Cell/Lithium Battery System by Dong Li, Xiaobo Zhong, Yuanwu Xu, Chongyang Wei, Song Zhao, Jianhua Jiang, Zhonghua Deng, Xiaowei Fu, Xi Li

“…In this paper, considering the strong coupling between variables, we use a particle filter algorithm to jointly estimate the state of charge and state of health. …”
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Explosion Resistance of Three-Dimensional Mesoscopic Model of Complex Closed-Cell Aluminum Foam Sandwich Structure Based on Random Generation Algorithm by Zhen Wang, Wen Bin Gu, Xing Bo Xie, Qi Yuan, Yu Tian Chen, Tao Jiang

“…Then, the algorithm of generating aluminum foam with random pore size and random wall thickness is written by Python and Fortran, and the mesh model of random polyhedral particles and random wall thickness was established by the algorithm read in by TrueGrid software. …”
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Trip route optimization based on bus transit using genetic algorithm with different crossover techniques: a case study in Konya/Türkiye by Akylai Bolotbekova, Huseyin Hakli, Ayse Beskirli

“…In order to select the most appropriate crossover operator of the genetic algorithm, the performances of seven methods, namely One Point Crossover (OX1), Two Point Crossover (OX2), Position Based Crossover (PBX), Order Based Crossover (OBX), Partially Mapped Crossover (PMX), Cycle Crossover (CX) and Inversion Crossover (IX) are tested on the real-world problem in Konya/Türkiye. …”
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Multi-step Prediction of Monthly Sediment Concentration Based on WPT-ARO-DBN/WPT-EPO-DBN Model by GAO Xuemei, CUI Dongwen

“…Accurate multi-step sediment concentration prediction is of significance for regional soil erosion control,flood control and disaster reduction.To improve the multi-step prediction accuracy of sediment concentration and the prediction performance of the deep belief network (DBN),this paper proposes a multi-step prediction model of monthly sediment concentration by combining the artificial rabbit optimization (ARO) algorithm,eagle habitat optimization (EPO) algorithm,and DBN based on wavelet packet transform (WPT).The model is validated using time series data of monthly sediment concentration from Longtan Station in Yunnan Province.Firstly,WPT is employed to decompose the time series data of the monthly sediment concentration of the case in three layers,and eight more regular subsequence components are obtained.Secondly,the principles of ARO and EPO algorithms are introduced,and hyperparameters such as the neuron number in the hidden layer of DBN are optimized by ARO and EPO.Meanwhile,WPT-ARO-DBN and WPT-EPO-DBN prediction models are built,and WPT-PSO (particle swarm optimization)-DBN and WPT-DBN are constructed for comparative analysis.Finally,four models are adopted to predict each subsequence component,and the predicted values are superimposed to obtain the multi-step prediction results of the final monthly sediment concentration.The results are as follows.① WPT-ARO-DBN and WPT-EPO-DBN models have satisfactory prediction effects on the monthly sediment concentration of the case from one step ahead to four steps ahead.This yields sound prediction results for five steps ahead.The prediction effect for six steps ahead and seven steps ahead is average,and the prediction accuracy for eight steps ahead is poor and cannot meet the prediction accuracy requirements.② The multi-step prediction performance of WPT-ARO-DBN and WPT-EPO-DBN models is superior to WPT-PSO-DBN models and far superior to WPT-DBN models,with higher prediction accuracy,better generalization ability,and larger prediction step size.③ ARO and EPO can effectively optimize DBN hyperparameters,improve DBN prediction performance,and have better optimization effects than PSO.Additionally,WPT-ARO-DBN and WPT-EPO-DBN models can give full play to the advantages of WPT,new swarm intelligence algorithms and the DBN network and improve the multi-step prediction accuracy of monthly sediment concentration,and the prediction accuracy decreases with the increasing prediction steps.…”
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Coverage path planning for multi-AUV considering ocean currents and sonar performance by Xukai Mu, Wei Gao

“…To address the CPP of multiple AUVs (multi-AUV) considering both sonar performance and ocean currents, we propose a new integrated algorithm based on the improved Dijkstra algorithm, Particle Swarm Optimization (PSO), and the ELKAI Solve. …”
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Experimental study on solution possibilities of multiextremal optimization problems through heuristic methods by Rudolf A. Neydorf, Ivan V. Chernogorov, Orkhan Takhir Yarakhmedov, Victor V. Polyakh

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KFCM-PSOTD : An Imputation Technique for Missing Values in Incomplete Data Classification by Muhaimin Ilyas, Syaiful Anam, Trisilowati Trisilowati

“…In addition, the PSOTD algorithm is used as an optimization tool to boost the KFCM's performance. …”
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