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). Streamflow forecasting using a hybrid LSTM-PSO approach: the case of Seyhan Basin. Retrieved May 24, 2026, from https://4ort.xyz/entity/streamflow-forecasting-using-a-hybrid-lstm-pso-approach-the-case-of-seyhan-basin
MLA“Streamflow forecasting using a hybrid LSTM-PSO approach: the case of Seyhan Basin.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/streamflow-forecasting-using-a-hybrid-lstm-pso-approach-the-case-of-seyhan-basin.
BibTeX@misc{4ortxyz_streamflow-forecasting-using-a-hybrid-lstm-pso-approach-the-case-of-seyhan-basin_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Streamflow forecasting using a hybrid LSTM-PSO approach: the case of Seyhan Basin}}, year = {2026}, url = {https://4ort.xyz/entity/streamflow-forecasting-using-a-hybrid-lstm-pso-approach-the-case-of-seyhan-basin}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Streamflow forecasting using a hybrid LSTM-PSO approach: the case of Seyhan Basin — https://4ort.xyz/entity/streamflow-forecasting-using-a-hybrid-lstm-pso-approach-the-case-of-seyhan-basin (retrieved 2026-05-24)
