Predictive Analysis of Industrial Engineering Energy Technology and International Economic Cooperation with KPCA-SVM

The industrial engineering energy industry is in development and has broad development prospects. With international economic cooperation it can promote its development and structural optimization, so conducting relevant evaluations is particularly important. However, the current practical research on industrial engineering energy technology and international economic cooperation is not yet mature, and there is a lack of corresponding models and methods. Therefore, this article standardizes the data on industrial engineering energy technology development, analyzes it using the KPCA-SVM model, and finds the switching point with international economic cooperation practices. Firstly, matrix analysis is conducted on industrial engineering energy technology data and international economic cooperation practice evaluation data to identify the main trends and indicators of energy technology development using KPCA. Then, SVM models are used for classification prediction. Finally, the expected results of industrial engineering energy technology and international economic cooperation are predicted by adjusting the prediction parameters and classification parameters. And through simulation experiments, the verification results show that KPCA can recognize 90% of the characteristics in industrial engineering energy technology, SVM model can reduce 35% of redundant data, and KPCA-SVM model can improve the integration of energy technology and international economic cooperation, with an improvement rate of over 35%. So, the KPCA-SVM model can achieve massive data processing of industrial engineering energy technology, accurately predict international economic cooperation, and promote cooperation between the two.