Computerised analysis of non-conjugate spiral bevel gear mesh using an advanced and fast-converging tooth contact model by Maksat Temirkhan, Andas Amrin

“…However, most of these methods rely on a discretized approach, resulting in approximate solutions and the use of additional optimization algorithms, such as particle swarm optimization to find the initial contact or grid representation of the tooth surface composed of nodal points. …”
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A method for urban high-voltage distribution network partitioning and energy storage planning by LIU Zhengmao, ZHU Sicheng, HUANG Zhongliang, JIANG Jianjie, ZHU Yitao, ZHANG Youbing, PAN Hongwu

“…A multi-objective particle swarm optimization （MOPSO） is employed to obtain the Pareto frontier， and the rank sum ratio （RSR） is used to determine the optimal site and capacity of energy storage for each partition. …”
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Coordinated Planning of Medium-Voltage and Low-Voltage Flexible Interconnection for Distribution Networks with High Proportion of Distributed Generation by Hanmei PENG, Tang YIN, Qianhao XIAO, Mao TAN, Yongxin SU, Hui LI

“…A hybrid algorithm based on adaptive particle swarm optimization and second-order cone programming is adopted for solution. …”
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Integrated Energy Management in Small-Scale Smart Grids Considering the Emergency Load Conditions: A Combined Battery Energy Storage, Solar PV, and Power-to-Hydrogen System by Hossein Jokar, Taher Niknam, Moslem Dehghani, Pierluigi Siano, Khmaies Ouahada, Mokhtar Aly

“…Compared to conventional evolutionary methods like particle swarm optimization, non-dominated sorting genetic algorithm III, and biogeography-based optimization, the proposed model exhibits remarkable improvements, outperforming them by 11.4%, 5.6%, and 11.6%, respectively. …”
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Analysis and prediction of infectious diseases based on spatial visualization and machine learning by Yunyun Cheng, Yanping Bai, Jing Yang, Xiuhui Tan, Ting Xu, Rong Cheng

“…Then, autoregressive integrated moving average model (ARIMA), extreme learning machine (ELM), support vector regression (SVR), wavelet neural network (Wavelet), recurrent neural network (RNN) and long short-term memory (LSTM) were used to predict COVID-19 epidemic data in Guangdong Province, China; And the prediction performance of each model was compared through prediction accuracy indicators. Finally, a multi algorithm fusion learning model based on stacking technology is proposed to address the problem of poor generalization ability of single algorithm models in prediction; Furthermore, radial basis function network (RBF) was used as a two-level meta learner to fuse the above models, and particle swarm optimization (PSO) was used to optimize RBF parameters to reduce generalization error. …”
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Probabilistic back analysis method for determining surrounding rock parameters of deep hard rock tunnel by WU Zhong-guang, WU Shun-chuan

“…Second, a multi-output support vector machine (MSVM) was optimized by particle swarm optimization (PSO) algorithm, and an intelligent response surface model was established to reflect the nonlinear mapping relationship between back-analyzed parameters and field monitoring data. …”
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A Mixed Integer Formulation and an NSGA-II for the Cumulative Capacitated Vehicle Routing Problem With Priority Indexes by Karina Corona-Gutierrez, Samuel Nucamendi-Guillen, Iris Martinez-Salazar, J. Marcos Moreno-Vega

“…Likewise, a comparative analysis was conducted between the proposed approaches and a Particle Swarm Optimization algorithm already presented in the literature. …”
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Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

“…To solve this problem, this paper proposes a hybrid method that combines multimodal data-aware attacks with Light Gradient Boosting Machine (LightGBM) and Support Vector Regression (SVR) agent models. By using Particle Swarm Optimization-Genetic Algorithm (PSO-GA) for optimal architecture search and combining the dynamic adaptability of Deep Q-Network (DQN) algorithm, this method can automatically identify the most suitable GNN architecture for power data monitoring, thereby improving the adaptive detection and defense efficiency of the system. …”
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Enhancing Fault Detection in AUV-Integrated Navigation Systems: Analytical Models and Deep Learning Methods by Huibao Yang, Bangshuai Li, Xiujing Gao, Bo Xiao, Hongwu Huang

“…Furthermore, to improve the detection of gradual faults, artificial intelligence-based fault detection methods were also explored. Specifically, the particle swarm optimization (PSO) algorithm was employed to optimize the hyperparameters of a long short-term memory (LSTM) neural network, leading to the development of a PSO-LSTM fault detection model. …”
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Machine Learning Prediction of Mechanical Properties for Marine Coral Sand–Clay Mixtures Based on Triaxial Shear Testing by Bowen Yang, Kaiwei Xu, Zejin Wang, Haodong Sun, Peng Cui, Zhiming Chao

“…Utilizing this dataset, several predictive models were developed, including a standard Support Vector Machine (SVM), an SVM optimized via Genetic Algorithm (GA-SVM), an SVM enhanced by Particle Swarm Optimization (PSO-SVM), and a hybrid model incorporating Logical Development Algorithm preprocessing a SVM model (LDA-SVM). …”
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Classification and Recognition of Soybean Quality Based on Hyperspectral Imaging and Random Forest Methods by Man Chen, Zhichang Chang, Chengqian Jin, Gong Cheng, Shiguo Wang, Youliang Ni

“…The model parameters were optimized using particle swarm optimization (PSO) and differential evolution (DE) algorithms to improve performance. …”
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Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO-BP Neural Network by Tianpeng Zhang, Pengfei Ji, Dayong Tian, Rui Xu

“…The Fenton oxidation process is used to treat kitchen anaerobic wastewater, and the effects of H2O2 dosage, Fe2+ dosage, reaction time and pH value on chemical oxygen demand (COD) degradation efficiency are explored. The improved particle swarm optimization (IPSO) algorithm is used to optimize the back propagation (BP) neural network, and a prediction model of COD degradation is established based on IPSO-BP neural network. …”
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Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis by Javad Shirani Shamsabadi, Saeid Ansari Mahyari, Mostafa Ghaderi-Zefrehei

“…The aim of this study was to compare the performance of three adaptive neuro-fuzzy inference systems (ANFIS) classification methodologies in classifying mastitis in Holstein dairy cattle: gradient descent (GD)-based ANFIS (GD-ANIFIS), particle swarm optimization (PSO)-based ANFIS (PSO-ANFIS) and genetic algorithm (GA)-based ANFIS (GA-ANFIS). …”
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VIS/NIR Spectroscopy as a Non-Destructive Method for Evaluation of Quality Parameters of Three Bell Pepper Varieties Based on Soft Computing Methods by Meysam Latifi Amoghin, Yousef Abbaspour-Gilandeh, Mohammad Tahmasebi, Mohammad Kaveh, Hany S. El-Mesery, Mariusz Szymanek, Maciej Sprawka

“…Raw spectral data were initially modeled using partial least squares regression (PLSR). To optimize wavelength selection, support vector machines (SVMs) were combined with genetic algorithms (GAs), particle swarm optimization (PSO), ant colony optimization (ACO), and imperial competitive algorithm (ICA). …”
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Height of Hydraulic Fracture Zone Based on PSO_LSSVM Model by Hebin Zhang, Tingting Wang, Bin Wu, Haijun Feng

“…At the same time, this study develops a particle swarm optimization algorithm based on adaptive inertia weight and a least squares support vector machine model to achieve height prediction of water conducting fracture zones. …”
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A Robust Control Strategy for Distributed Generations in Islanded Microgrids by esmaeel rokrok, fariba shavakhi zavareh, jafar soltani, mahmoud reza shakarami

“…All the parameters of controllers are derived via particle swarm optimization (PSO) algorithm in order to minimize an appropriate cost function. …”
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A Coordinated Pumped Storage Dual Compensated Hydro Governor with PSS Action to Damp Electromechanical Power Oscillations by Narayan Nahak, Samarjeet Satapathy

“…Again, subject to critical oscillatory unstable conditions, the DCG is coordinated with PSS through a multiobjective function employing a new modified Differential Evolutionary-Particle swarm optimization (MDEPSO) algorithm. Different case studies with sudden and random SPV and wind penetrations being executed with the proposed controller considering a two area four machine and 39 bus multimachine system with pumped storage hydro units to observe system oscillations are considered. …”
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Heat Storage Decoupling Method Based on Coordinated Load Scheduling Model by Yi LEI, Mingzhen LIU, Kaimin LIN

“…The power-heat coupling characteristics of CHP units are firstly studied; and then a heat-power decoupling scheme is formulated for wind power-heat storage compensation, and a multi-objective load-dispatching model is built with the objective of minimizing both the operation cost and pollutant emission of the power system; finally, the corrected multi-objective particle swarm optimization algorithm is used to solve the model, and the diversity of the Pareto set is maintained by using niche method. …”
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Dynamic Stability for Seismic-Excited Earth Retaining Structures Following a Nonlinear Criterion by Jingshu Xu, Jiahui Deng, Zemian Wang, Linghao Qi, Yundi Wang

“…With the application of a genetic algorithm and particle swarm optimization, the optimal upper bound solutions of active earth pressure coefficients were obtained. …”
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The Adaptive-Clustering and Error-Correction Method for Forecasting Cyanobacteria Blooms in Lakes and Reservoirs by Xiao-zhe Bai, Hui-yan Zhang, Xiao-yi Wang, Li Wang, Ji-ping Xu, Jia-bin Yu

“…In addition, the number of nearest neighbors used for modeling was optimized by particle swarm optimization. Finally, a fuzzy linear regression method based on error-correction was used to revise the model dynamically near the operating point. …”
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