CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model by Li Jie, Wang Shuai, Lan Hai, Wang Zhiyong

“…To solve the engineering problem of power loss in wet brakes under non-braking conditions, taking into consideration the influence of the lubricating oil in the clearance of friction pairs on the drag torque of the friction pair, making use of the strong nonlinear fitting ability of the sparrow-search-algorithm-back propagation (SSA-BP) neural network, and taking the no-load operating condition of wet brakes as the input variable and the drag torque as the output variable, an approximate model of wet brakes is established. …”
Get full text

Innovative Study on Volatility Prediction Model for New Energy Stock Indices by Yanguo Li, Chao Long

“…The model comprises three components: variational mode decomposition (VMD), sparrow search algorithm (SSA), and echo state network (ESN). …”
Get full text

Light-GBM based minority oversampling model using biomedical data analysis for breast cancer classification by Mukesh Soni, Mohammed Wasim Bhatt, Paul Ofori-Amanfo

“…In the Sparrow Search Algorithm (SSA), piecewise linear chaotic map (PWLCM), novel inertia weights, and a new longitudinal-lateral crossover algorithm are introduced for improvement, followed by the application of the improved SSA algorithm for automatic parameter optimization of Light-GBM. …”
Get full text

Short-term Power Prediction of Photovoltaic Power Generation Based on LSTM and Error Correction by ZHU Tao, LI Junwei, ZHU Yuanfu, YE Zhiming, TANG Yi

Get full text

An improved deep learning model for soybean future price prediction with hybrid data preprocessing strategy by Dingya CHEN, Hui LIU, Yanfei LI, Zhu DUAN

“…Finally, the high frequency component is decomposed secondarily using variational mode decomposition optimized by beluga whale optimization algorithm. In the deep learning prediction stage, a deep extreme learning machine optimized by the sparrow search algorithm was used to obtain the prediction results of all subseries and reconstructs them to obtain the final soybean future price prediction results. …”
Get full text

Forecasting and decision making of firm’s financial indicators based on the SSA-MLP-BPNN model by Xin Xu

“…In recent years, with the development of artificial intelligence and machine learning technologies, more and more researchers begin to apply these technologies to the prediction and decision-making of enterprise financial indicators.In this paper, we develop a model combined with the Sparrow Search Algorithm(SSA), Multilayer Perceptron(MLP) and Back Propagation Neural Network(BPNN) (SSA-MLP-BPNN model) to study the prediction and decision-making of financial indicators of listed companies in China. …”
Get full text

Optimization strategies for public health education based on ISSA and information system technology by Zhanyu Ye, Yifei Li, Yan Zhang

Get full text

Key technologies of robotic arm motion control based on compound control and improved SCSO. by Kuo Hu

“…To meet the high-precision motion control demand, this study proposes a robotic arm motion control technology integrating composite control and an improved sandcat swarm optimization algorithm. The algorithm is enhanced by introducing the Iterative chaotic iterative mapping and sparrow warning mechanism. …”
Get full text

A Short-Term Load Forecasting Method Considering Multiple Factors Based on VAR and CEEMDAN-CNN-BILSTM by Bao Wang, Li Wang, Yanru Ma, Dengshan Hou, Wenwu Sun, Shenghu Li

Get full text

Fault Diagnosis and Data Reconstruction of Temperature Sensors for Wind Turbine Stator Winding by Ling Zhou, Qiancheng Zhao, Jinhui Zeng, Anfeng Zhu, Xiafei Long, Ling He

Get full text

LightGBM hybrid model based DEM correction for forested areas. by Qinghua Li, Dong Wang, Fengying Liu, Jiachen Yu, Zheng Jia

“…To overcome these shortcomings, this paper cites an improved SSA search algorithm that incorporates the ingestion strategy of the FA algorithm to increase the diversity of solutions and global search capability, the Firefly Algorithm-based Sparrow Search Optimization Algorithm (FA-SSA algorithm) is introduced. …”
Get full text

GIS partial discharge fault diagnosis method based on SGMD-LSTM by Zhang Yun, Zhang Chao, Zhang Shiyong, Ma Pengchi, Yang Guang, Ding Hao

Get full text

Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data. by Jin Wang, Shihan Ma, Qing Lv, Qiang Li

“…In the study, the Extreme Gradient Boosting tree (XGBoost) model is used to identify the base model to create a reliable predictive model for population dynamic monitoring. The sparrow search algorithm (SSA) is investigated to obtain more reasonable parameters of XGBoost to improve forecast accuracy. …”
Get full text

Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…Moreover, This study develops the proposed EffiXNet, a more refined version of EfficientNet augmented with self-attention mechanisms, dynamic convolutions, improved normalization methods, and Sparrow Search Optimization Algorithm for hyperparameter optimization. …”
Get full text

Early Warning for the Construction Safety Risk of Bridge Projects Using a RS-SSA-LSSVM Model by Gang Li, Ruijiang Ran, Jun Fang, Hao Peng, Shengmin Wang

“…The proposed model integrates a rough set (RS), the sparrow search algorithm (SSA), and the least squares support vector machine (LSSVM). …”
Get full text

Understanding the evolutionary processes and causes of groundwater drought using an interpretable machine learning model by Zhiyuan Gan, Xianjun Xie, Chunli Su, Weili Ge, Hongjie Pan, Liangping Yang

“…We employed machine learning models and the Shapley Additive Explanation (SHAP), a game theory-based interpretability method, to understand and predict the evolution of groundwater drought by evaluating eight models with SHAP analysis in the West Liao River Plain (WLRP), with a semi-arid climate. The research showed: (1) The XGBoost model, optimized by the Sparrow Search Algorithm (SSA), achieved the highest performance (AUC: 0.922, F1-score: 0.84). (2) SHAP analysis revealed that the Standardized Precipitation Evapotranspiration Index (SPEI) at 12- and 24-month scales (SPEI12 and SPEI24) were key predictors, with long-term meteorological drought causing delayed groundwater drought, exacerbated by over-extraction and urbanization. …”
Get full text

Predicting the Spatial Distribution of Geological Hazards in Southern Sichuan, China, Using Machine Learning and ArcGIS by Ruizhi Zhang, Dayong Zhang, Bo Shu, Yang Chen

“…Several machine learning models were evaluated, including random forest, XGBoost, and CatBoost, with model optimization performed using the Sparrow Search Algorithm (SSA) to enhance prediction accuracy. …”
Get full text

Optimization of grading rings for 1000 kV dry-type air-core shunt reactor based on hybrid RBFNN–Kriging surrogate model by Yiqin Liu, Liang Xie, Dongyang Li, Yunpeng Liu, Kexin Liu, Gang Liu

“…Aiming to reduce the maximum electric field strength of the reactor, this paper proposes a hybrid surrogate model that combines Radial Basis Function Neural Network (RBFNN) and the Kriging model to optimize the configuration of grading rings. First, the sparrow search algorithm is used to optimize the hyperparameters of the RBFNN. …”
Get full text

Fault Diagnosis of Lithium-Ion Batteries Based on the Historical Trajectory of Remaining Discharge Capacity by Jiuchun Jiang, Bingrui Qu, Shuaibang Liu, Huan Yan, Zhen Zhang, Chun Chang

Get full text

The Fermentation Degree Prediction Model for Tieguanyin Oolong Tea Based on Visual and Sensing Technologies by Yuyan Huang, Jian Zhao, Chengxu Zheng, Chuanhui Li, Tao Wang, Liangde Xiao, Yongkuai Chen

“…In contrast, the data fusion models demonstrated superior performance, with the MAE reduced to 2.232–2.783, the RMSE reduced to 2.693–3.969, and R² increased to 0.982–0.991, confirming that feature fusion enhanced characterization accuracy. Finally, the Sparrow Search Algorithm (SSA) was applied to optimize the data fusion models. …”
Get full text