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https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://schema.org/description In this paper, a novel weighted-combination-of-components (WCC) method is proposed for modeling and forecasting trend and seasonal time series, and such a method is based on decomposition model which regards the time series as the weighted combination of trend, seasonality and other components. Specifically, the Holt's two-parameter exponential smoothing (HTPES) method is improved (for short, the IHTPES method) to evaluate the trend with linearly declining increments; and the multiple sine functions decomposition (MSFD) method is developed to evaluate the seasonality. Then the weighted combination of the evaluations is obtained to estimate the global time series. Numerical experiment results substantiate the effectiveness and superiority of the proposed WCC method in terms of modeling and forecasting time series from the NN3 competition. https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://schema.org/encodingFormat application/ld+json https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://schema.org/endTime 2014-01-01 https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://schema.org/identifier https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://schema.org/name Time Series Forecasting via Weighted Combination of Trend and Seasonality Respectively with Linearly Declining Increments and Multiple Sine Functions https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ 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https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Concept trend https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#FieldOfResearch earth sciences https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Lemma WCC https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Lemma experiment https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Lemma forecasting https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Lemma increment https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Lemma seasonality https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Lemma sine https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Lemma time series https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Lemma trend https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#NASA mathematical and computer sciences https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Phrase WCC method https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Phrase forecasting time series https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Phrase forecasting trend https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Phrase multiple sine functions decomposition https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Phrase time series forecasting https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Sentence In this paper, a novel weighted-combination-of-components (WCC) method is proposed for modeling and forecasting trend and seasonal time series, and such a method is based on decomposition model which regards the time series as the weighted combination of trend, seasonality and other components. https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Sentence Numerical experiment results substantiate the effectiveness and superiority of the proposed WCC method in terms of modeling and forecasting time series from the NN3 competition. https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#Sentence Time Series Forecasting via Weighted Combination of Trend and Seasonality Respectively with Linearly Declining Increments and Multiple Sine Functions. https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ http://w3id.org/ro/earth-science#distributionCategory Open access https://w3id.org/ro-id/0a257616-b449-4845-923f-e269c5379dff/ 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