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The invention provides an intelligent power supply state detection method and system for a lead-acid battery of a communication base station, which can use a lead-acid battery pack as a load of a communication base station for supplying a constant voltage. . The invention provides an intelligent power supply state detection method and system for a lead-acid battery of a communication base station, which can use a lead-acid battery pack as a load of a communication base station for supplying a constant voltage. . The uninterrupted operation of wireless communication services relies heavily on the stability of power supply systems for Base Transceiver Stations (BTS). This study is dedicated to predicting potential failure indicators in BTS power systems using deep neural network architectures, such as. . In mobile telecom networks, Base Transceiver Station (BTS) is a key infrastructure that connects customers with the mobile network. BTSs are geographically scattered across the networks service area and thousands of fault indicating alarms are generated by a typical BTS on a daily basis. Compared with the buck topology, the new topology can trackloadcurrentbetter,thusthepowerprovidedbylinearamplifierisreducedand overall efficiency of the system is improved. By using Machine Learning techniques to predict power system failures, ECONET Zimbabwe can take proactive measures to prevent disruptions in service, resulting in improved. .
