Home ›
Entities
› academia
› Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel
Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel
Research article (Mining of Mineral Deposits, 2020) · cited 25× · AI/ML
Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel
Summary
Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel is a scholarly article[1].
Key Facts
Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel'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). Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel. Retrieved May 24, 2026, from https://4ort.xyz/entity/prediction-of-tunnel-boring-machine-penetration-rate-using-ant-colony-optimization-bee-colony-optimization-and-the-parti
MLA“Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/prediction-of-tunnel-boring-machine-penetration-rate-using-ant-colony-optimization-bee-colony-optimization-and-the-parti.
BibTeX@misc{4ortxyz_prediction-of-tunnel-boring-machine-penetration-rate-using-ant-colony-optimization-bee-colony-optimization-and-the-parti_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel}}, year = {2026}, url = {https://4ort.xyz/entity/prediction-of-tunnel-boring-machine-penetration-rate-using-ant-colony-optimization-bee-colony-optimization-and-the-parti}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel — https://4ort.xyz/entity/prediction-of-tunnel-boring-machine-penetration-rate-using-ant-colony-optimization-bee-colony-optimization-and-the-parti (retrieved 2026-05-24)