Confused about activation functions in neural networks? This video breaks down what they are, why they matter, and the most common types — including ReLU, Sigmoid, Tanh, and more! #NeuralNetworks ...

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 ...

You’ll often hear plastic pollution referred to as a problem. But the reality is that it’s multiple problems. Depending on the properties we need, we form plastics out of different polymers, each of ...

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 ...

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 ...

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 ...

Ballbots are versatile robotic systems with the ability to move around in all directions. This makes it tricky to control their movement. In a recent study, a team has proposed a novel proportional ...

The proposed controller for ballbot devices enhances the adaptability to dynamic environments via self-learning and self-adjusting characteristics. Ballbot is a unique kind of robot with great ...