Estimating wind energy at a specific wind site depends on how well the real wind data in that area can be represented using an appropriate distribution function. In fact, wind sites differ in the extent to which their wind data can be represented from one region to another, despite the widespread use of the Weibull function in representing the wind speed in various wind locations in the world. In this study, a new probability distribution model (normal PDF) was tested to implement wind speed at several wind locations in Jordan. The results show high compatibility between this model and the wind resources in Jordan. Therefore, this model was used to estimate the values of the wind energy and the extracted energy of wind turbines compared to those obtained by the Weibull PDF. Several artificial intelligence techniques were used (GA, BFOA, SA, and a neuro-fuzzy method) to estimate and predict the parameters of both the normal and Weibull PDFs that were reflected in conjunction with the ac
An anonymous reader quotes a report from NBC News: New research (PDF) conducted by a professor at University of Pennsylvania s Wharton School found that the artificial intelligence-driven chatbot GPT-3 was able to pass the final exam for the school s Master of Business Administration (MBA) program. .
New research conducted by a professor at University of Pennsylvania’s Wharton School found that the artificial intelligence-driven chatbot GPT-3 was able to.
New research conducted by a professor at University of Pennsylvania’s Wharton School found that the artificial intelligence-driven chatbot GPT-3 was able to.