Repository logo
 

AI Applications in Characterizing and Enhancing Optical Fiber Performance

dc.contributor.authorZediri ,Akila /Rehab ,Nardjes /Encadré par Gouder, Soraya
dc.date.accessioned2025-07-23T02:28:30Z
dc.date.available2025-07-23T02:28:30Z
dc.date.issued2025-06-10
dc.description.abstractOptical fibers are among the most important modern technologies in the field of communications, enabling high-speed and efficient data transmission over long distances with low signal loss and high immunity to electromagnetic interference. These fibers operate based on the principle of total internal reflection, transmitting light through a central core surrounded by a cladding with a lower refractive index. In recent years, AI has played an increasingly significant role in enhancing the performance of optical fibers. Techniques such as machine learning and ANNs networks have contributed to data analysis, fault detection, performance prediction under various conditions, and the optimization of fiber design through accurate simulations and intelligent forecasting of optical properties. The integration of AI with optical fiber technologies represents a major step toward smarter, more flexible, and more efficient communication systems.en_US
dc.description.provenanceSubmitted by Tom User (dspacest@univ-tebessa.dz) on 2025-07-23T02:28:30Z No. of bitstreams: 1 Zediri Akila.pdf: 2723813 bytes, checksum: b56b33b1e5f5febf1357835811dbfd9d (MD5)en
dc.description.provenanceMade available in DSpace on 2025-07-23T02:28:30Z (GMT). No. of bitstreams: 1 Zediri Akila.pdf: 2723813 bytes, checksum: b56b33b1e5f5febf1357835811dbfd9d (MD5) Previous issue date: 2025-06-10en
dc.identifier.urihttp//localhost:8080/jspui/handle/123456789/12950
dc.language.isoenen_US
dc.publisherUniversité Echahid Cheikh Larbi Tebessi - Tebessaaen_US
dc.subjectPhotonic Crystal Fibers Artificial Intelligence (AI) Machine Learning Deep Learning Deep Neural Networken_US
dc.titleAI Applications in Characterizing and Enhancing Optical Fiber Performanceen_US
dc.typeThesisen_US

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Zediri Akila.pdf
Size:
2.6 MB
Format:
Adobe Portable Document Format
Description:

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: