Real-Time Height Measurement for Moving Pedestrians by Wenju Zhou, Fulong Yao, Wei Feng, Haikuan Wang

“…Secondly, a difference-particle swarm optimization (D-PSO) algorithm is proposed to remove the complex background and reduce the noises. …”
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Optimizing energy cost in the residential sector through home energy management systems in a smart grid environment by Nabeeha Qayyum, Umar Jamil, Anzar Mahmood

“…This research aims to optimize power usage by reducing peak loads and electricity costs through the integration of RESs, such as solar or photovoltaic (PV) systems, while considering grid limitations, PV capacity, appliance ON/OFF schedules, and time-of-use tariffs. A genetic algorithm (GA) based optimization technique was employed to evaluate the performance of a HEMS and validated with particle swarm optimization (PSO) technique under identical initial conditions for each appliance and their corresponding energy pricing over different periods. …”
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An Adaptive 24 GHz PSO-Based Optimized VCO in Next-Generation Wireless Sensor Networks by Khizra Tariq, Unal Aras, Tahesin Samira Delwar, Muhammad Nadeem Ali, Yangwon Lee, Jee-Youl Ryu, Byung-Seo Kim

“…In this paper, the adaptive particle swarm optimization (PSO) algorithm incorporates adaptive scaling to speed up the optimization process. …”
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A novel hybrid model for predicting the bearing capacity of piles by Li Tao, Xinhua Xue

“…The main objective of this study is to propose a hybrid model coupling least squares support vector machine (LSSVM) with an improved particle swarm optimization (IPSO) algorithm for the prediction of bearing capacity of piles. …”
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Sparse Array Mutual Coupling Reduction by C. Larmour, N. Buchanan, V. Fusco, M. Ali Babar Abbasi

“…The paper conducts a comprehensive comparison of multiple array design optimisation techniques, including genetic algorithm, covariance matrix adaptation evolution strategy, particle swarm optimisation, trust-region framework, Nelder-Mead simplex algorithm, interpolated Quasi-Newton, and classic Powell. …”
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Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling by Bo Li, Yaohua Liao, Siyang Liu, Chao Liu, Zhensheng Wu

“…Traditional short-term power load-forecasting methods have certain limitations in accuracy and stability, especially when dealing with complex weather and voltage changes. To improve the prediction accuracy, this paper proposes a short-term power load-forecasting model of a regional power grid based on multi-source parameter coupling with a long short-term memory neural network (LSTM) and adopts an improved particle swarm optimization (IPSO) algorithm to optimize the LSTM network. …”
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Chaotic chimp-mountain gazelle optimized FOPID control for frequency regulation in islanded airport microgrids with heterogeneous energy systems by Odelu P., Chandan Kumar Shiva, Sachidananda Sen, Vedik Basetti, Chandra Sekhar Reddy

“…Simulation results demonstrates that the CCMGO optimized fractional order proportional-integral-derivative controller exhibits better performances compared to the conventional genetic algorithm and particle swarm optimization based controllers, as well as contemporary metaheuristic algorithms like grey wolf optimizer and whale optimization algorithm. …”
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A study on monthly sales forecasting of new energy vehicles in urban areas using the WOA-BiGRU model. by Xiangtu Li

“…Its prediction results are compared with those of the particle swarm optimization (PSO) algorithm. The research findings are as follows: The growth of NEV sales has reversed the declining trend of overall automobile sales in China; Cities with higher NEV sales are predominantly concentrated in four major economic hubs--the Pearl River Delta, Yangtze River Delta, Beijing-Tianjin-Hebei region, and Chengdu-Chongqing. …”
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Calculation Methods for the Permeability Coefficient of Concrete Face Rockfill Dam with Cracks by Zhongwen Shi, Zhongru Wu, Chongshi Gu, Bo Chen, Hailong Zhang, Wenzhong Yin, Bangbin Wu

“…Moreover, an inversion algorithm based on particle swarm optimization and support vector machine was proposed and applied. …”
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Optimal Operation of Microgrid Considering Photovoltaic,Storage and Turbine by XIANG Hongwei, CHANG Xiqiang, L Menglin, XING Zhanli, WANG Han

“…Constraints include power balance constraints, etc. The improved particle swarm optimization algorithm is used to solve the problem. …”
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SIC-Free Based Indoor Two-User NOMA-VLCP System by Jianli Jin, Qianlong Shang, Jianping Wang, Huimin Lu, Danyang Chen, Dongmei Yang

“…The particle swarm optimization (PSO) algorithm is employed to construct a joint optimization function that optimizes the power allocation factor of the two users and the roll-off coefficient of the square-root-raised-cosine(SRRC) filter. …”
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Research on Deformation Prediction of Foundation Pit Based on PSO-GM-BP Model by Dongge Cui, Chuanqu Zhu, Qingfeng Li, Qiyun Huang, Qi Luo

“…The prediction optimized by the particle swarm algorithm is more accurate and has more substantial applicability. …”
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Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework by Saleem Malik, Chandrakanta Mahanty, Jnanaranjan Mohanty, Krunal Vaghela, T. Narmadha, R. Sivaranjani, Javed Khan Bhutto, Saiful Islam, Anwar Khan, Amanuel Zewdie

“…The NeuroEvoClass algorithm mixes evolutionary strategies inspired by swarm intelligence and artificial neural networks (ANN) to improve student performance prediction in Phase II. …”
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A Novel Approach to Pine Nut Classification: Combining Near-Infrared Spectroscopy and Image Shape Features with Soft Voting-Based Ensemble Learning by Yueyun Yu, Xin Huang, Danjv Lv, Benjamin K. Ng, Chan-Tong Lam

“…Experimental validation on a dataset comprising seven pine nut varieties demonstrated that, compared to particle swarm optimization (PSO) and the genetic algorithm (GA), the IBiEO-SP algorithm improved average classification accuracy by 5.7% (<i>p</i> < 0.01, Student’s <i>t</i>-test) under four spectral preprocessing methods (MSC, SNV, SG1, and SG2). …”
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A Novel PAPR in OTFS Systems Through ISSA-PTS and ISPR Techniques by Gerges Mansour Salama, Amira A. Mohamed, Aziza I. Hussein, M. Mourad Mabrook

“…This study introduces two novel PAPR reduction techniques: a hybrid approach combining the Improved Salp Swarm Algorithm (ISSA) with Partial Transmit Sequence (PTS) and an innovative Iterative Sub-block Phase Rotation (ISPR) method. …”
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A Methodology for Situation Assessing of Space-Based Information Networks by Sai Xu, Jun Liu, Jiawei Tang, Xiangjun Liu, Zhi Li

“…The proposed method first applies principal component analysis for dimensionality reduction, followed by pre-labeling situational factor data using an improved K-means clustering algorithm. The on-orbit assessment of individual satellites is then performed using a particle swarm optimization-support vector machine algorithm. …”
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Hardware-in-loop implementation of an adaptive MPPT controlled PV-assisted EV charging system with vehicle-to-grid integration by Surabhi Singh, Hari Om Bansal

“…This paper developed and compared perturb and observe (P&O), Particle swarm optimization (PSO), and hybrid PSO + Adaptive neuro-fuzzy inference system (ANFIS) based algorithm for MPPT. …”
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Analyzing Student Graduation and Dropout Patterns Using Artificial Intelligence and Survival Strategies by Behrouz Alefy, Vahid Babazadeh

“…Weevil Damage Optimization Algorithm, Black Widow Optimization Algorithm, and Phasor Particle Swarm Optimization form the core of 3 optimization approaches. …”
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Application of deep reinforcement learning in parameter optimization and refinement of turbulence models by Zhan Zhang

“…The DDPG optimization method significantly reduced the MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) of the WPC, and its optimization effect was significantly better than the GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) methods.…”
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Comparative Analysis of Bio-Inspired Enhancement Techniques for Localization in 2D Wireless Sensor Networks by Rabhi Seddik

“…This study conducts a comparative evaluation of three bio-inspired optimization algorithms for node localization: Particle Swarm Optimization (PSO), Fruit Fly Optimization Algorithm (FOA), and Drop Mongoose Optimization Algorithm (DMOA). …”
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