Home › Entities › academia › In-Situ early anomaly detection and remaining useful lifetime prediction for high-power white LEDs with distance and entropy-based long short-term memory recurrent neural networks

In-Situ early anomaly detection and remaining useful lifetime prediction for high-power white LEDs with distance and entropy-based long short-term memory recurrent neural networks

Research article (Expert Systems with Applications, 2023) · cited 24× · AI/ML
academia openalex:W4387267138
Press Enter · cited answer in seconds

In-Situ early anomaly detection and remaining useful lifetime prediction for high-power white LEDs with distance and entropy-based long short-term memory recurrent neural networks

Summary

In-Situ early anomaly detection and remaining useful lifetime prediction for high-power white LEDs with distance and entropy-based long short-term memory recurrent neural networks is a scholarly article[1].

Key Facts

  • In-Situ early anomaly detection and remaining useful lifetime prediction for high-power white LEDs with distance and entropy-based long short-term memory recurrent neural networks'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). In-Situ early anomaly detection and remaining useful lifetime prediction for high-power white LEDs with distance and entropy-based long short-term memory recurrent neural networks. Retrieved May 24, 2026, from https://4ort.xyz/entity/in-situ-early-anomaly-detection-and-remaining-useful-lifetime-prediction-for-high-power-white-leds-with-distance-and-ent
MLA “In-Situ early anomaly detection and remaining useful lifetime prediction for high-power white LEDs with distance and entropy-based long short-term memory recurrent neural networks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/in-situ-early-anomaly-detection-and-remaining-useful-lifetime-prediction-for-high-power-white-leds-with-distance-and-ent.
BibTeX @misc{4ortxyz_in-situ-early-anomaly-detection-and-remaining-useful-lifetime-prediction-for-high-power-white-leds-with-distance-and-ent_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{In-Situ early anomaly detection and remaining useful lifetime prediction for high-power white LEDs with distance and entropy-based long short-term memory recurrent neural networks}}, year = {2026}, url = {https://4ort.xyz/entity/in-situ-early-anomaly-detection-and-remaining-useful-lifetime-prediction-for-high-power-white-leds-with-distance-and-ent}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): In-Situ early anomaly detection and remaining useful lifetime prediction for high-power white LEDs with distance and entropy-based long short-term memory recurrent neural networks — https://4ort.xyz/entity/in-situ-early-anomaly-detection-and-remaining-useful-lifetime-prediction-for-high-power-white-leds-with-distance-and-ent (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/in-situ-early-anomaly-detection-and-remaining-useful-lifetime-prediction-for-high-power-white-leds-with-distance-and-ent · Last refreshed: