Home ›
Entities
› academia
› Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural networks
Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural networks
Research article (Energy and Buildings, 2017) · cited 100× · AI/ML
Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural networks
Summary
Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural networks is a scholarly article[1].
Key Facts
Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural networks'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). Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural networks. Retrieved May 24, 2026, from https://4ort.xyz/entity/comparative-assessment-of-low-complexity-models-to-predict-electricity-consumption-in-an-institutional-building-linear-r
MLA“Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural networks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/comparative-assessment-of-low-complexity-models-to-predict-electricity-consumption-in-an-institutional-building-linear-r.
BibTeX@misc{4ortxyz_comparative-assessment-of-low-complexity-models-to-predict-electricity-consumption-in-an-institutional-building-linear-r_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural networks}}, year = {2026}, url = {https://4ort.xyz/entity/comparative-assessment-of-low-complexity-models-to-predict-electricity-consumption-in-an-institutional-building-linear-r}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Comparative assessment of low-complexity models to predict electricity consumption in an institutional building: Linear regression vs. fuzzy modeling vs. neural networks — https://4ort.xyz/entity/comparative-assessment-of-low-complexity-models-to-predict-electricity-consumption-in-an-institutional-building-linear-r (retrieved 2026-05-24)
