FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3004113099> ?p ?o ?g. }

• W3004113099 endingPage "6003" @default.
• W3004113099 startingPage "5994" @default.
• W3004113099 abstract "Partial periodic time series are found in many areas. However, many partial periodic time-series prediction methods are unable to capture the feature dependence within the fluctuation of data. In this article, a multiseries featural long short-term memory (LSTM) is proposed. A novel template-matching method is used to extract specific periodic characteristics adaptively and restack the 1-D time series into multiseries featural structure data. The extended series is fed into a multivariable LSTM network to exploit the feature-temporal patterns for predictions. To enhance the long-term prediction performance, a period correction method is used to reduce the iteration errors caused by multistep prediction. To demonstrate the effectiveness of the proposed method, two classical partial periodic data sets and two byproduct gas data sets are studied here. Our results demonstrate that the proposed prediction method has advantages on prediction accuracy, especially for the critical structural features, that satisfies the requirements of the practically viable prediction." @default.
• W3004113099 created "2020-02-07" @default.
• W3004113099 creator A5024970317 @default.
• W3004113099 creator A5046597133 @default.
• W3004113099 creator A5061884304 @default.
• W3004113099 creator A5062542913 @default.
• W3004113099 date "2020-09-01" @default.
• W3004113099 modified "2023-10-17" @default.
• W3004113099 title "Multiseries Featural LSTM for Partial Periodic Time-Series Prediction: A Case Study for Steel Industry" @default.
• W3004113099 cites W1801605453 @default.
• W3004113099 cites W1993261349 @default.
• W3004113099 cites W2040297119 @default.
• W3004113099 cites W2063885094 @default.
• W3004113099 cites W2064675550 @default.
• W3004113099 cites W2079473768 @default.
• W3004113099 cites W2111685619 @default.
• W3004113099 cites W2120390927 @default.
• W3004113099 cites W2133969552 @default.
• W3004113099 cites W2248342699 @default.
• W3004113099 cites W2297334139 @default.
• W3004113099 cites W2391139807 @default.
• W3004113099 cites W2426723127 @default.
• W3004113099 cites W2528991849 @default.
• W3004113099 cites W2553191309 @default.
• W3004113099 cites W2575125657 @default.
• W3004113099 cites W2588479775 @default.
• W3004113099 cites W2591180046 @default.
• W3004113099 cites W2595984151 @default.
• W3004113099 cites W2597948870 @default.
• W3004113099 cites W2604099671 @default.
• W3004113099 cites W2605620338 @default.
• W3004113099 cites W2613328025 @default.
• W3004113099 cites W2623776817 @default.
• W3004113099 cites W2716916105 @default.
• W3004113099 cites W2754252319 @default.
• W3004113099 cites W2764101711 @default.
• W3004113099 cites W2774610454 @default.
• W3004113099 cites W2792326773 @default.
• W3004113099 cites W2802436364 @default.
• W3004113099 cites W2896661041 @default.
• W3004113099 cites W2928373814 @default.
• W3004113099 cites W2961525083 @default.
• W3004113099 cites W2964010366 @default.
• W3004113099 doi "https://doi.org/10.1109/tim.2020.2967247" @default.
• W3004113099 hasPublicationYear "2020" @default.
• W3004113099 type Work @default.
• W3004113099 sameAs 3004113099 @default.
• W3004113099 citedByCount "22" @default.
• W3004113099 countsByYear W30041130992020 @default.
• W3004113099 countsByYear W30041130992021 @default.
• W3004113099 countsByYear W30041130992022 @default.
• W3004113099 countsByYear W30041130992023 @default.
• W3004113099 crossrefType "journal-article" @default.
• W3004113099 hasAuthorship W3004113099A5024970317 @default.
• W3004113099 hasAuthorship W3004113099A5046597133 @default.
• W3004113099 hasAuthorship W3004113099A5061884304 @default.
• W3004113099 hasAuthorship W3004113099A5062542913 @default.
• W3004113099 hasConcept C105795698 @default.
• W3004113099 hasConcept C11413529 @default.
• W3004113099 hasConcept C117312493 @default.
• W3004113099 hasConcept C119857082 @default.
• W3004113099 hasConcept C121332964 @default.
• W3004113099 hasConcept C127413603 @default.
• W3004113099 hasConcept C133731056 @default.
• W3004113099 hasConcept C138885662 @default.
• W3004113099 hasConcept C143724316 @default.
• W3004113099 hasConcept C151406439 @default.
• W3004113099 hasConcept C151730666 @default.
• W3004113099 hasConcept C153180895 @default.
• W3004113099 hasConcept C154945302 @default.
• W3004113099 hasConcept C165064840 @default.
• W3004113099 hasConcept C2776401178 @default.
• W3004113099 hasConcept C2776537626 @default.
• W3004113099 hasConcept C33923547 @default.
• W3004113099 hasConcept C41008148 @default.
• W3004113099 hasConcept C41895202 @default.
• W3004113099 hasConcept C52622490 @default.
• W3004113099 hasConcept C61797465 @default.
• W3004113099 hasConcept C62520636 @default.
• W3004113099 hasConcept C76155785 @default.
• W3004113099 hasConcept C86803240 @default.
• W3004113099 hasConceptScore W3004113099C105795698 @default.
• W3004113099 hasConceptScore W3004113099C11413529 @default.
• W3004113099 hasConceptScore W3004113099C117312493 @default.
• W3004113099 hasConceptScore W3004113099C119857082 @default.
• W3004113099 hasConceptScore W3004113099C121332964 @default.
• W3004113099 hasConceptScore W3004113099C127413603 @default.
• W3004113099 hasConceptScore W3004113099C133731056 @default.
• W3004113099 hasConceptScore W3004113099C138885662 @default.
• W3004113099 hasConceptScore W3004113099C143724316 @default.
• W3004113099 hasConceptScore W3004113099C151406439 @default.
• W3004113099 hasConceptScore W3004113099C151730666 @default.
• W3004113099 hasConceptScore W3004113099C153180895 @default.
• W3004113099 hasConceptScore W3004113099C154945302 @default.
• W3004113099 hasConceptScore W3004113099C165064840 @default.
• W3004113099 hasConceptScore W3004113099C2776401178 @default.
• W3004113099 hasConceptScore W3004113099C2776537626 @default.
• W3004113099 hasConceptScore W3004113099C33923547 @default.

• next