Home ›
Entities
› academia
› A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process
A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process
Research article (Neurocomputing, 2017) · cited 41× · AI/ML
A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process
Summary
A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process is a scholarly article[1].
Key Facts
A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-hybrid-time-series-prediction-model-based-on-recurrent-neural-network-and-double-joint-linearnonlinear-extreme-learnin
MLA“A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-hybrid-time-series-prediction-model-based-on-recurrent-neural-network-and-double-joint-linearnonlinear-extreme-learnin.
BibTeX@misc{4ortxyz_a-hybrid-time-series-prediction-model-based-on-recurrent-neural-network-and-double-joint-linearnonlinear-extreme-learnin_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process}}, year = {2026}, url = {https://4ort.xyz/entity/a-hybrid-time-series-prediction-model-based-on-recurrent-neural-network-and-double-joint-linearnonlinear-extreme-learnin}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process — https://4ort.xyz/entity/a-hybrid-time-series-prediction-model-based-on-recurrent-neural-network-and-double-joint-linearnonlinear-extreme-learnin (retrieved 2026-05-24)