AlSi10Mg alloy is an extensively utilised material having good mechanical qualities. The laser powder bed fusion procedure has been applied for fabricating the aluminium alloy (AlSi10Mg) plates in this research. Different exposure periods and scan techniques were applied in this work to measure the average roughness. Results demonstrate that the energy density grew and roughness reduced at first and then improved. Furthermore, there were considerable differences in roughness throughout the created faces. At 125 J/mm3 and 180 J/mm3, excellent surface quality was attained. By this experiment, it was noticed that the direction of scan, wiper movement, and gas flow are the key parameters.

Currently, weather forecasting is the most commonly discussed topic by social and economic activists. It is also attracting widespread interest due to its application in various public and private sectors that include marine, agriculture, air traffic, and forestry. Recent developments have made climatic changes happen at a dramatic rate, making old methods of weather forecasting less effective, more hectic, and unreliable. Improved and efficient methods of weather prediction are needed to overcome these difficulties. This paper describes machine learning approaches using artificial neural networks to predict the weather of a particular city and compare the different weather conditions in different cities. We demonstrate empirically that Artificial Neural Networks produce very low deviations hence providing nearly accurate results for weather forecasts on a daily basis.