Research on Big Data Power Load Based on Neural Network Prediction Model
DOI:
https://doi.org/10.54097/hset.v64i.11257Keywords:
RF_XGBoost prediction, grid search, Random Forest Feature Vector Selection, Coefficient of variation.Abstract
The price of sailboats will change with time and market changes. Reasonable prediction and evaluation of the price of second-hand sailboats can have a certain impact on the price of second-hand sailboats. The better ones in the area are for sale.The paper established the RF_XGBoost second-hand sailboats price prediction model, determined the feature variables from the type of sailboat, regional economy, the random forest algorithm is used to select the feature variables, and the optimization is based on the grid search algorithm after the data normalization process obtained the minimum value.After analyzing the characteristic variables it is found that the region has little influence on the listed price, and thus has little influence on the features. Meanwhile, the Pearson correlation analysis between the variables and the price shows that there is a weak negative correlation consistency between the region and the type of sailing boats.
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References
A. Chongterdtoonskul and W. Tharmmaphornphilas, "Offshore Crew Boat Sailing Time Forecast using Regression Models," 2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA), Bangkok, Thailand, 2020, pp. 883-889.
S. Guo, "Dynamic simulation and Analysis of Propulsion Performance of Intelligent Unmanned Boat," 2021 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS), Shenyang, China, 2021, pp. 653-655.
R. M. Balinda, S. Allamsetty and T. R. Choudhury, "Sizing an Electric Propulsion System for Catamaran Passenger Boat in Uganda," 2022 IEEE India Council International Subsections Conference (INDISCON), Bhubaneswar, India, 2022, pp. 1-6.
Cai Qiuru. Electric Vehicle Price Prediction Based on XGBoost Integrated Learning Algorithm [J]. Journal of Jiangsu Institute of Technology, 2020, 26(06): 33-43.
J. Song, L. Jin, Y. Xie and C. Wei, "Optimized XGBoost based sparrow search algorithm for short-term load forecasting," 2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE), SC, USA, 2021, pp. 213-217.
Ouyang Han, Liao Wenqi, Tian Qiuhong. Electric Vehicle Price Prediction Based on Machine Learning [J]. Guangxi Quality Supervision Herald, 2021, No.244(04):204-206.
Li Fuqiang, Peng Haili, Yang Xi, Zhang Wenjing. Used car price prediction model and impact analysis based on deep learning [J]. Journal of Automotive Engineering, 2021,11(05):379-385.
R. Oji, S. F. Razavi, S. A. Dehsorkh, A. Hariri, H. Asheri and R. Hosseini, "ParsiNorm: A Persian Toolkit for Speech Processing Normalization," 2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS), Tehran, Iran, Islamic Republic of, 2021, pp. 1-5.
Zheng Jie. Prediction of Used Car Price Based on Random Forest and XGBoost Algorithm [J]. Digital Technology and Application, 2021, 39(06): 90-93+188.
J. Jin, C. Zhang and Q. -J. Zhang, "An enhanced multi-circuit optimization approach for identification of microwave filter parameters," 2016 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO), Beijing, China, 2016, pp. 1-2.
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