• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.3
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• pp.225-230
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• 2020

Recently, with the miniaturization of GIS, there is a need for the miniaturization of spacers as accessories. Miniaturized spacers make it difficult to secure adequate insulation distances, resulting in a more concentrated electric field at the triple junction of high-voltage (HV) conductor-insulator (spacer)-insulation gas (SF₆), which is a weakness in GIS. Therefore, by introducing a new concept design technology, functionally graded material (FGM), which is recently applied to various materials and parts industries, three-dimensional control of the dielectric constant distribution in a spacer can be expected to alleviate triple-junction electric field occupancy and improve insulation performance. In this study, we propose an optimized model using NSGA-II to optimize the permittivity distribution of FGM applied spacer.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.121-128
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• 2024

Demand forecasting is a critical element of revenue management in the tourism industry. Since the 2010s, with the globalization of the tourism industry and the increase of different forms of marketing and information sharing, such as SNS, forecasting has become difficult due to non-linear activities and unstructured information. Various forecasting models for resolving the problems have been studied, and ML models have been used effectively. In this study, we applied the feature selection technique (NSGA3) to time series models and compared their performance. In hotel demand forecasting, it was found that the TCN model has a high forecasting performance of MAPE 9.73% with a performance improvement of 7.05% compared to no feature selection. The results of this study are expected to be useful for decision support through improved forecasting performance.