Home ›
Entities
› academia
› A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network
A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network
Research article (AIChE Journal, 2020) · cited 44× · AI/ML
A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network
Summary
A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network is a scholarly article[1].
Key Facts
A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network'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 novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-novel-adaptive-sampling-based-methodology-for-feasible-region-identification-of-compute-intensive-models-using-artific
MLA“A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-novel-adaptive-sampling-based-methodology-for-feasible-region-identification-of-compute-intensive-models-using-artific.
BibTeX@misc{4ortxyz_a-novel-adaptive-sampling-based-methodology-for-feasible-region-identification-of-compute-intensive-models-using-artific_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network}}, year = {2026}, url = {https://4ort.xyz/entity/a-novel-adaptive-sampling-based-methodology-for-feasible-region-identification-of-compute-intensive-models-using-artific}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network — https://4ort.xyz/entity/a-novel-adaptive-sampling-based-methodology-for-feasible-region-identification-of-compute-intensive-models-using-artific (retrieved 2026-05-24)