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 explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
Stimulant medications like methylphenidate boost circulating dopamine levels and are effective treatments for attention-deficit hyperactivity disorder (ADHD), but they do not work for everyone. Here, ...
The blood pump is an implantable device with strict performance requirements. Any effective structural improvement will help to improve the treatment of patients. However, the research of blood pump ...
Radial Basis Function Neural Networks (RBFNNs) are a type of neural network that combines elements of clustering and function approximation, making them powerful for both regression and classification ...
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