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@article{166847,
        author = {Madhumitha. F and Geethakumari. D and Gokulram. H and Nawaz Sherief M},
        title = {STUDY ON ADVANCE AI METHODS USED IN SEISMOLOGY – MACHINE LEARNING SYSTEM AND DEEP LEARNING SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {2},
        pages = {2255-2264},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=166847},
        abstract = {In this current world predicting earthquake is critical for seismic risk assessment, prevention and safe design of major structures. Due to the complex nature of seismic events, it is challengeable to efficiently identify the earthquake response and extract indicative features from the continuously detected seismic data. These challenges severely impact the performance of traditional seismic prediction models and obstacle the development of seismology in general. Taking their advantages in data analysis, artificial intelligence (AI) techniques have been utilized as powerful statistical tools to tackle these issues. This typically involves processing massive detected data with severe noise and also the vibration on earth’s surface to enhance the seismic performance of structures. From extracting meaningful sensing data to unveiling seismic events that are below the detection level, AI in ML, Deep Learning system, etc. assists in identifying unknown features to more accurately predicting the earthquake activities. In this focus paper, the history of seismology is analysed and I provide an overview of the recent methods like AI studies in seismology and evaluate the performance of the major AI techniques including machine learning and deep learning in seismic data analysis.},
        keywords = {Seismology, Artificial Intelligence, Machine Learning System, Deep Learning System.},
        month = {September},
        }