A comprehensive system for demonstrating measurable performance improvements through systematic prompt engineering using information-theoretic metrics and statistical validation.

Graduate Program in Biotechnology, Federal University of Pará, Belém 66075-110, Brazil Graduate Program in Process Engineering, Federal University of Pará, Belém 66075-110, Brazil Faculty of Chemical ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

Abstract: In recent years, numerous recurrent neural network (RNN) models have been reported for solving time-dependent nonlinear optimization problems. However, few existing RNN models simultaneously ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks efficiently. #RMSProp #Optimization #DeepLearning Zelensky makes major concession to ...

1 Faculty of Land Resources Engineering, Kunming University of Science and Technology Kunming, Kunming, China 2 Pangang Group Mining Company Limited Panzhihua, Panzhihua, Sichuan, China The stability ...

The CM PERFORMING ARTS CENTER is holding Main Stage auditions for MONTY PYTHON’S SPAMALOT on Sunday, November 9th and Monday, November 10th at 7:30 PM. Callbacks will be by invitation only. Please ...

Is your feature request related to a problem? Please describe. It would be nice to have the Marion 2008 [1] nonlinear adjustment to the PVWatts V5 DC power model (pvlib.pvsystem.pvwatts_dc) available ...