Prediction of Sonar Rocks Against Mines Using Machine Learning

Sonar technology is essential for detecting objects underwater and is used in many different applications, such as marine security. The Underwater mines, that are used for the Defense System of naval, that provides good protection, yet they also cause danger for marine life and submarines since the explosives might be mistaken for harmless rocks. To avoid this misidentification, we need an accurate algorithm to find the item since it is quite dangerous to have a mistake. To gain good accuracy, we need more precise data in order to get the results accurately. In this paper, our Ideology highlights the existence of mines under the water surface which uses sonar dataset. The Sonar signal data is used to identify the varied frequency of underwater objects at more different angles. We have developed a predictive system model based on their accuracy. Prediction models are then used to identify between the “Rock” and “Mine” categories. These prediction models are built using Machine Learning Classification algorithms and Python.