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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국마린엔지니어링학회 Journal of Advanced Marine Engineering and Technology (JAMET) 한국마린엔지니어링학회지 제42권 제2호
- 발행연도
- 2018.2
- 수록면
- 127 - 135 (9page)
- DOI
- 10.5916/jkosme.2018.42.2.127
이용수
초록· 키워드
오류제보하기
In this paper, we propose a new forecasting approach that finds a nearest-neighbor optimum for forecasting. It blends the advantages of subsample use (k-nearest neighbor, rolling window, etc.) and entire sample use. Basically, it belongs to the range of nearest neighbor methods but is different from them in that it also considers the entire sample, which can help to yield less variance in test error than other subsample methods. To improve forecasting accuracy, we also used a modified least squares method in the process of this forecasting approach. From simulation tests, we were able to verify that this approach yielded less test error than other methods that do not adopt this approach. Empirical verification using time-series data on the ship accident also supported that this approach is able to improve forecasting accuracy. In addition, we were able to verify that the test errors obtained from this approach were less than the residuals obtained from fitting using the actual future value in many cases. A new parameter controlling a weight between the subsample and the entire sample is introduced, and the forecasting performance may depend on how this parameter can be efficiently used.
목차
Abstract
1. Introduction
2. Methods
3. Numerical results
4. Conclusion
References
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