Machine Learning based Prediction of Parameters that Influence Life on Mars

One of the world's most challenging scientific and technological problems is weather forecasting, a major application in meteorology. This study analyzes different ways to forecast minimum and maximum temperature, humidity, pressure and wind speed using data mining approaches. Weather forecasting is challenging due to complex meteorological phenomena and a lack of observations and historical data. Many variables in weather events are impossible to count and quantify. As communication methods have progressed, weather forecast expert systems have been able to combine and exchange resources, resulting in the development of a hybrid system. Despite these advancements in weather forecasting, these expert systems cannot be completely dependable because weather forecasting is the primary issue. Weather forecasting is meteorologists attempt to forecast weather conditions in the future and forecast weather situations that may occur. Temperature, wind, humidity, pressure, and data set size all influence the weather condition characteristics. Weather forecasting's purpose is to give knowledge to the people and governments, which they may use to prevent the loss of lives and infrastructure. In the context of this research, it can be utilized to determine whether or not the circumstances on Mars are suitable for human survival.