Real-world optimization problems often require an external “modeling engine” that computes fitnesses or data that are then input to an objective function. These programs often have much longer ...
Of the many feats achieved by artificial intelligence (AI), the ability to process images quickly and accurately has had an especially impressive impact on science and technology. Now, researchers in ...
Multifidelity optimization can inform decision-making during process development and reduce the number of experiments ...
Abstract: The Airline Scheduling Problem (ASP) has significant economic and operational value in air trans portation management. However, its complexity and dynamics make traditional mixed integer ...
Distributed Integrated Energy Microgrid, as a key infrastructure for the low-carbon transition of regional energy systems, faces critical challenges in achieving optimal operation—primarily due to ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Abstract: Multiplicative updates have been widely used in approximative nonnegative matrix factorization (NMF) optimization because they are convenient to deploy. Their convergence proof is usually ...
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