Home ›
Entities
› academia
› Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States
Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States
Research article (Environmental Science and Pollution Research, 2022) · cited 40× · AI/ML
Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States
Summary
Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States is a scholarly article[1].
Key Facts
Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States'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). Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States. Retrieved May 24, 2026, from https://4ort.xyz/entity/development-of-new-computational-machine-learning-models-for-longitudinal-dispersion-coefficient-determination-case-stud
MLA“Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/development-of-new-computational-machine-learning-models-for-longitudinal-dispersion-coefficient-determination-case-stud.
BibTeX@misc{4ortxyz_development-of-new-computational-machine-learning-models-for-longitudinal-dispersion-coefficient-determination-case-stud_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States}}, year = {2026}, url = {https://4ort.xyz/entity/development-of-new-computational-machine-learning-models-for-longitudinal-dispersion-coefficient-determination-case-stud}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States — https://4ort.xyz/entity/development-of-new-computational-machine-learning-models-for-longitudinal-dispersion-coefficient-determination-case-stud (retrieved 2026-05-24)
