M. Al-Sakhnini, Mahmoud, Kalra, D, Ali, Liaqat, Afzaal, Farheen, Pervaiz, Madiha and Khan, Muhammad Farrukh (2022) Distributed Search Engine Query Optimization Using Artificial Neural Network. In: 2022 International Conference on Cyber Resilience (ICCR), 06-07 October 2022, Dubai, United Arab Emirates.
Full text not available from this repository. (Request a copy)Abstract
In this research, we propose a Distributed Search Engine Query Optimization (DSEQO) based sensor network concept for instantaneous forest fire exposure. The sensor network may identify and predict forest fire more sharp than the outdated satellite-based prediction method. The research mainly defines the information gathering and managing in sensor networks for real-time forest fire detection. To predict the real-time fire identification, an ANN technique is utilized to in-network information processing. After simulation it was seen that the suggested approach gives better results with LM approach in terms of Accuracy and Miss Rate.
Affiliation: | Skyline University College |
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SUC Author(s): | M. Al-Sakhnini, Mahmoud and Kalra, D |
All Author(s): | M. Al-Sakhnini, Mahmoud, Kalra, D, Ali, Liaqat, Afzaal, Farheen, Pervaiz, Madiha and Khan, Muhammad Farrukh |
Item Type: | Conference or Workshop Item (Paper) |
Uncontrolled Keywords: | Query processing, Forestry, Artificial neural networks, Prediction methods, Information processing, Search engines, Data processing |
Subjects: | B Information Technology > BM Artificial Intelligence |
Divisions: | Skyline University College > School of IT |
Depositing User: | Mr Mosys Team |
Date Deposited: | 26 Jan 2024 14:55 |
Last Modified: | 26 Jan 2024 14:55 |
URI: | https://research.skylineuniversity.ac.ae/id/eprint/780 |
Publisher URL: | https://doi.org/10.1109/ICCR56254.2022.9995958 |
Publisher OA policy: | |
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