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Bidding Control Price Pricing Mechanism of Power Transmission Project Materials Based on SVM-Bagging Integrated Learning

Year: 2024
Type: conference-paper
Abstract: Transmission and substation engineering is a key link in the electric power system, which bears the important responsibility of safely and efficiently delivering electricity from the power station to the regions that use electricity. The current bidding control price of equipment and material prices for power transmission and transformation projects mainly relies on historical purchasing unit prices and experience, and the control price set is often much different from the actual price. Unreasonable control prices may lead to an imbalance in the project budget, resulting in reduced bidding competition and affecting project costs and quality. Material prices are affected by a variety of internal and external factors; price fluctuations are frequent and unpredictable; and previous forecasting models are difficult to adapt to price changes. This study responds to price changes more flexibly by introducing influencing factors that reflect time and market demand, such as producer price index and regional per capita GDP, and uses gray correlation to compare the correlation between different factors and material prices to determine the importance of each factor. Using the key influencing factors, combined with Support Vector Machine (SVM) and Bagging integration methods, the material price prediction model is constructed, and the model is validated using the procurement data of high-voltage switchgear, which has a high procurement frequency. Finally, the SVM-Bagging integrated model is compared with the prediction results of the SVM model to prove that the model has excellent prediction accuracy and good adaptability.
DOI: 10.1145/3718491.3718582
Authors: Nan Shang, Shengjie Wang, Mengdan Chen, Weijun Wang
Language: English
Open Access status: gold
OpenAlex ID: W4409095091
FWCI:
Cites: 7
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Related to: 10