Year: 2025
Type: article
Abstract: In recent years, artificial intelligence (AI) technologies have emerged as a promising tool for enhancing earthquake statistics evaluation and improving earthquake prediction structures. This paper evaluates the utility of AI in earthquake facts evaluation, earthquake prediction, and hazard evaluation. Various research has demonstrated the effectiveness of device getting to know and deep learning algorithms, inclusive of Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and Support Vector Machines (SVM), in processing and reading seismic alerts. AI techniques have been utilized to identify styles in earthquake records, predict earthquakes, and assess seismic hazards greater accurately as compared to standard techniques. Additionally, AI-primarily based early warning systems for earthquakes have been advanced, providing timely signals and improving disaster preparedness. Research additionally highlights the combination of Explainable AI (XAI) to enhance the interpretability of seismic models, thereby improving decision-making in seismic risk evaluation and management. The software of AI in seismic studies introduces a brand-new measurement to earthquake monitoring and mitigation, promising quicker, greater accurate, and cost-effective solutions.
Authors: Enas Altalhe, A'laa Khalid, Heba Mansour, Kolthom Ahmed
Institution: Omar Al-Mukhtar University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409493850