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This research article presents a method for detecting anomalies in geothermal operational assets using the Locality-Sensitive Hashing (LSH) algorithm, which enhances traditional anomaly detection techniques. By analyzing historical sensor data from geothermal power plants, the LSH algorithm improves the accuracy of detecting operational irregularities, facilitating early maintenance interventions. The study emphasizes the importance of effective asset management in ensuring reliable energy generation and re

Author

李杰

Language

EN