The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The present study investigates the usability of oxygenated fuel on the performance and exhaust emissions of a Diesel engine fueled with adulterated Diesel. In view of the engine experimentations, an Artificial Intelligence (AI) based Artificial Neural Network (ANN) model has been developed to predict outputs such as brake thermal efficiency (Bth), brake specific energy consumption (BSEC), oxides of...
The increasing trend in building sector's energy demand calls for reliable and robust energy consumption forecasting models. This study aims to compare prediction capabilities of five different intelligent system techniques by forecasting electricity consumption of an administration building located in London, United Kingdom. These five techniques are; Multiple Regression (MR), Genetic Programming...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.