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Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...

Confused about cost functions in neural networks? In this video, we break down what cost functions are, why they matter, and which types are best for different applications—from classification to ...

Abstract: Neural networks have increasingly been utilized in electric drive systems to enhance modeling, control, and optimization. These data-driven techniques enable accurate predictions of complex ...

Multi-robot systems are increasingly deployed in complex, dynamic environments such as environmental monitoring, industrial automation, and search-and-rescue missions. The coordination of such systems ...

Aquaculture is recognized as a critical component of global food security and economic development, playing an indispensable role in meeting nutritional needs and supporting livelihoods worldwide.

ABSTRACT: We solve numerically an eigenvalue elliptic partial differential equation (PDE) ranging from two to six dimensions using the generalized multiquadric (GMQ) radial basis functions (RBFs). Two ...

This repository gathers all known Kolmogorov-Arnold Networks (including those I developed) from various sources. These networks are implemented for image classification on some simple image ...

The proposed controller for ballbot devices enhances the adaptability to dynamic environments via self-learning and self-adjusting characteristics.Péter Fankhauser from Openverse/Wikimedia Commons ...