Home ›
Entities
› academia
› Exploring spatial and temporal importance of input features and the explainability of machine learning-based modelling of water distribution systems
Exploring spatial and temporal importance of input features and the explainability of machine learning-based modelling of water distribution systems
Research article (Digital Chemical Engineering, 2024) · cited 13× · AI/ML
Exploring spatial and temporal importance of input features and the explainability of machine learning-based modelling of water distribution systems
Summary
Exploring spatial and temporal importance of input features and the explainability of machine learning-based modelling of water distribution systems is a scholarly article[1].
Key Facts
Exploring spatial and temporal importance of input features and the explainability of machine learning-based modelling of water distribution systems'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). Exploring spatial and temporal importance of input features and the explainability of machine learning-based modelling of water distribution systems. Retrieved May 24, 2026, from https://4ort.xyz/entity/exploring-spatial-and-temporal-importance-of-input-features-and-the-explainability-of-machine-learning-based-modelling-o
MLA“Exploring spatial and temporal importance of input features and the explainability of machine learning-based modelling of water distribution systems.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/exploring-spatial-and-temporal-importance-of-input-features-and-the-explainability-of-machine-learning-based-modelling-o.
BibTeX@misc{4ortxyz_exploring-spatial-and-temporal-importance-of-input-features-and-the-explainability-of-machine-learning-based-modelling-o_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Exploring spatial and temporal importance of input features and the explainability of machine learning-based modelling of water distribution systems}}, year = {2026}, url = {https://4ort.xyz/entity/exploring-spatial-and-temporal-importance-of-input-features-and-the-explainability-of-machine-learning-based-modelling-o}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Exploring spatial and temporal importance of input features and the explainability of machine learning-based modelling of water distribution systems — https://4ort.xyz/entity/exploring-spatial-and-temporal-importance-of-input-features-and-the-explainability-of-machine-learning-based-modelling-o (retrieved 2026-05-24)