Home ›
Entities
› academia
› Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand
Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand
Research article (International Journal of Environmental Research and Public Health, 2022) · cited 26× · AI/ML
Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand
Summary
Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand is a scholarly article[1].
Key Facts
Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand'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). Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand. Retrieved May 24, 2026, from https://4ort.xyz/entity/utilization-of-random-forest-classifier-and-artificial-neural-network-for-predicting-factors-influencing-the-perceived-u
MLA“Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/utilization-of-random-forest-classifier-and-artificial-neural-network-for-predicting-factors-influencing-the-perceived-u.
BibTeX@misc{4ortxyz_utilization-of-random-forest-classifier-and-artificial-neural-network-for-predicting-factors-influencing-the-perceived-u_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand}}, year = {2026}, url = {https://4ort.xyz/entity/utilization-of-random-forest-classifier-and-artificial-neural-network-for-predicting-factors-influencing-the-perceived-u}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand — https://4ort.xyz/entity/utilization-of-random-forest-classifier-and-artificial-neural-network-for-predicting-factors-influencing-the-perceived-u (retrieved 2026-05-24)
