Research on low-energy-consumption deployment of emergency UAV network for integrated communication-navigating-sensing by Li WANG, Qing WEI, Lianming XU, Yuan SHEN, Ping ZHANG, Aiguo FEI

“…In public emergencies such as accident relief, rescue workers are faced with challenges, such as poor communication, unstable navigating, and inaccurate disaster sensing.It is necessary to deploy an emergency unmanned aerial vehicle (UAV) network to guarantee the services of communication-navigating-sensing.Aiming at alleviating the problem of limited energy of UAV, a low-energy-consumption deployment of an emergency UAV network was first proposed for integrated communication-navigating-sensing (ICNS).The proposed scheme was able to realize network topology reconstruction and role cognition on demand.Then, a particle swarm algorithm based hierarchical matching decision-making algorithm was presented to jointly optimize three sub-problems, including the associations between UAVs and users, the resource allocation for multi-role UAV communications, and the UAV position.Simulation results show that the proposed ICNS scheme can achieve flexible adaptation of the multi-objective requirements and limited network resources, and dramatically reduce the demand for the number of UAVs and the deployment energy consumption.…”
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Investigation on the Role of Artificial Intelligence in Measurement System by P. A. Rezvy, Venkata Lakshmi Narayana Komanapalli

“…Hardware approach with soft computation has reduced non linearity error by 84.63% for thermocouple linearization, meanwhile novel hybrid approach using genetic algorithm (GA) and particle swarm optimization (PSO) combined with back propagation neural network (BPNN) have reduced mean absolute percentage error to 1.2 % for industrial weir than conventional hardware approaches using sensors and signal conditioning circuits but at higher computational cost. …”
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Wavenumber-Domain Joint Estimation of Rotation Parameters and Scene Center Offset for Large-Angle ISAR Cross-Range Scaling by Bakun Zhu, Weigang Zhu, Hongfeng Pang, Chenxuan Li, Lei Qui, Jinhai Yan, Fanyin Ma, Yijia Liu

“…Utilizing this model and the sensitivity of wavenumber-domain imaging to SCO, a joint estimation algorithm that combines particle swarm optimization (PSO) and image entropy evaluation is proposed, achieving accurate parameter estimation. …”
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A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance by Wenhui Zhang, Fan Gao, Shurui Sun, Qiuying Yu, Jinjun Tang, Bohang Liu

“…The second objective is the acceptable walking distance from the parking space to the destination. The particle swarm optimization (PSO) algorithm is used to solve this model. …”
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HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative Analysis by Dawit Kefale Wassie, Lebsework Negash Lemma, Abrham Tadesse Kassie

“…Therefore, a hybrid type of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), HGAPSO, has been formulated to find the best controllers’ parameters. …”
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A PSO-XGBoost Model for Predicting the Compressive Strength of Cement–Soil Mixing Pile Considering Field Environment Simulation by Jiagui Xiong, Yangqing Gong, Xianghua Liu, Yan Li, Liangjie Chen, Cheng Liao, Chaochao Zhang

“…Utilizing data mining on 84 sets of experimental data with various preparation parameter combinations, a prediction model for the as-formed strength of CSM Pile was developed based on the Particle Swarm Optimization-Extreme Gradient Boosting (PSO-XGBoost) algorithm. …”
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Voltage and Current Balancing of a Faulty Photovoltaic System Connected to Cascaded H-Bridge Multilevel Inverter by Kamel Djermouni, Ali Berboucha, Salah Tamalouzt, Djamel Ziane

“…For such a system, the particle swarm optimization (PSO) algorithm remains highly effective because it can easily handle the existence of multiple maxima simultaneously to provide the best possible solution. …”
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Trajectory Planning Method for Formation Rendezvous of Underactuated Multi-UUV Under Multiple Constraints by Qingzhe Wang, Da Xu, Xiaoran Liu, Gengshi Zhang, Zhao Han

“…In response to these issues, this paper presents a rendezvous points allocation method and a trajectory planning method for formation rendezvous based on dynamic parameter particle swarm optimization (DPPSO) optimizing polynomial trajectories. …”
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A deep decentralized privacy-preservation framework for online social networks by Samuel Akwasi Frimpong, Mu Han, Emmanuel Kwame Effah, Joseph Kwame Adjei, Isaac Hanson, Percy Brown

“…Our methodology employs a two-tier architecture: the first tier uses an elitism-enhanced Particle Swarm Optimization and Gravitational Search Algorithm (ePSOGSA) for optimizing feature selection, while the second tier employs an enhanced Non-symmetric Deep Autoencoder (e-NDAE) for anomaly detection. …”
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Research on Sensitivity Improvement Methods for RTD Fluxgates Based on Feedback-Driven Stochastic Resonance with PSO by Rui Wang, Na Pang, Haibo Guo, Xu Hu, Guo Li, Fei Li

“…Simulink is used to construct the sensor model of odd polynomial feedback control, and the Particle Swarm Optimization (PSO) algorithm is used to optimize the coefficients of the feedback function so that the sensor reaches a resonance state, thus reducing the noise interference and improving the sensitivity of the sensor. …”
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Approximate Inertial Manifold-Based Model Reduction and Vibration Suppression for Rigid-Flexible Mechanical Arms by Lisha Xu, Hua Deng, Chong Lin, Yi Zhang

“…A limited number of sinusoidal signals approximately combine the input signal, by using the particle swarm optimization algorithm to optimize the input signal, and the amplitude of the sinusoidal signal is corrected. …”
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Risk assessment of tunnel water inrush based on Delphi method and machine learning by Leizhi Dong, Qingsong Wang, Weiguo Zhang, Yongjun Zhang, Xiaoshuang Li, Fei Liu

“…Then, the Radial Basis Function (RBF) network, improved by the Locally Linear Embedding (LLE) algorithm and the Particle Swarm Optimization (PSO), is applied to predict the risk level. …”
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Investigation of Subband Electron Temperatures of Quantum Cascade Lasers by Chen Peng, Yuankun Sun, Liguo Zhu, Tao Chen, Gang Chen, Anping Yu, Sencheng Zhong, Pingwei Zhou, Zhaohui Zhai, Zeren Li

“…We show herein a method, based on the particle swarm optimization algorithm, to obtain the electron temperature of the conduction band in the active region of QCLs. …”
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An accurate model to predict drilling fluid density at wellbore conditions by Mohammad Ali Ahmadi, Seyed Reza Shadizadeh, Kalpit Shah, Alireza Bahadori

“…In this regard, a couple of particle swarm optimization (PSO) and artificial neural network (ANN) was utilized to suggest a high-performance model for predicting the drilling fluid density. …”
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Abnormal Electricity Consumption Behaviors Detection Based on Improved Deep Auto-Encoder by Nvgui LIN, Lanxiu HONG, Daoshan HUANG, Yang YI, Zhixuan LIU, Qifeng XU

“…To improve the feature extraction ability and the robustness of AE network, the sparse restrictions and the noise coding are introduced into the auto-encoder, and the hyper-parameters of AE network are optimized through the particle swarm optimization algorithm to improve the learning efficiency and generalization ability. …”
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Research on intelligent computing offloading model based on reputation value in mobile edge computing by Jin QI, Hairong SUN, Kun GONG, Bin XU, Shunyi ZHANG, Yanfei SUN

“…Aiming at the problem of high-latency,high-energy-consumption,and low-reliability mobile caused by computing-intensive and delay-sensitive emerging mobile applications in the explosive growth of IoT smart mobile terminals in the mobile edge computing environment,an offload decision-making model where delay and energy consumption were comprehensively included,and a computing resource game allocation model based on reputation that took into account was proposed,then improved particle swarm algorithm and the method of Lagrange multipliers were used respectively to solve models.Simulation results show that the proposed method can meet the service requirements of emerging intelligent applications for low latency,low energy consumption and high reliability,and effectively implement the overall optimized allocation of computing offload resources.…”
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Inversion Study of Hydrogeological Parameters for Metro Foundation Pit Confined Aquifiers Based on Surrogate Modeling by YE Ru, DI Honggui, ZHU Zhitai, ZHU Yilong, JIANG Bin, XIANG Longsheng, CHAI Dongsheng, YAO Qiyu

“…An LSTM (long- and short-term memory) deep learning model is introduced to build a surrogate model of confined aquifer water level variations. Combined with a particle swarm optimization algorithm and based on field-measured data, an inverse analysis of the confined aquifer permeability and storage coefficients is conducted. …”
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Research on Credit Default Prediction Model Based on TabNet-Stacking by Shijie Wang, Xueyong Zhang

“…The particle swarm algorithm is used to optimize the hyperparameter selection and achieve automatic parameter search. …”
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Small Modular Reactor based on NuScale with Thorium base by Diego M. E. Gonçalves, Marcelo Vilela da Silva, C. J. C. M. R. da Cunha, Giovanni L. Stefani

“…To meet substantial computational demands, they ran these simulations on the Lobo Carneiro supercomputer at NACAD/UFRJ. The team applied a Particle Swarm Optimization (PSO) algorithm to find the best seed-to-blanket volume ratio, thereby maximizing U-233 production and achieving a self-sustaining fuel cycle. …”
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A predictive framework using advanced machine learning approaches for measuring and analyzing the impact of synthetic agrochemicals on human health by Sahezpreet Singh, Puneet Kaur, Inderdeep Kaur, Gurpreet Singh, Satinder Kaur, Parminder Kaur

“…A custom loss function is leveraged to accurately predict the mortality cases and avoid misclassifications by penalizing the false negatives. Furthermore, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) used for model optimization. …”
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