Home › Entities › academia › Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor

Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor

Research article (Sensors, 2022) · cited 13× · AI/ML
academia openalex:W4309786507
Press Enter · cited answer in seconds

Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor

Summary

Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor is a scholarly article[1].

Key Facts

  • Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

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.

APA 4ort.xyz Knowledge Graph. (2026). Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor. Retrieved May 24, 2026, from https://4ort.xyz/entity/methodology-for-quantifying-volatile-compounds-in-a-liquid-mixture-using-an-algorithm-combining-b-splines-and-artificial
MLA “Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/methodology-for-quantifying-volatile-compounds-in-a-liquid-mixture-using-an-algorithm-combining-b-splines-and-artificial.
BibTeX @misc{4ortxyz_methodology-for-quantifying-volatile-compounds-in-a-liquid-mixture-using-an-algorithm-combining-b-splines-and-artificial_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor}}, year = {2026}, url = {https://4ort.xyz/entity/methodology-for-quantifying-volatile-compounds-in-a-liquid-mixture-using-an-algorithm-combining-b-splines-and-artificial}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor — https://4ort.xyz/entity/methodology-for-quantifying-volatile-compounds-in-a-liquid-mixture-using-an-algorithm-combining-b-splines-and-artificial (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/methodology-for-quantifying-volatile-compounds-in-a-liquid-mixture-using-an-algorithm-combining-b-splines-and-artificial · Last refreshed: