The diagram in Figure 2 gives you a rough idea of support vector regression for a scenario where there is just one predictor variable x. Each dot is a training data item. The red line is the linear ...

Optimization of concrete I-beams using a new hybrid glowworm swarm algorithm. Tatiana García-Segura I; Víctor YepesII, *; José V. Martí III; Julián Alcalá III. I Graduate Research Assistant, ICITECH, ...

Discover how Particle Swarm Optimization algorithm can accurately determine material parameters in elastic strain-energy functions. ... Implementation of Particle Swarm Optimization Algorithm in ...

Keywords: COVID-19 era, deep learning, backpropagation neural network, quantum step fruit fly optimization algorithm, quantum particle swarm optimization algorithm, quantum genetic algorithm Citation: ...

Evolutionary feature selection (FS) methods face the challenge of “curse of dimensionality” when dealing with high-dimensional data. Focusing on this challenge, this article studies a variable-size ...

For optimization of real time problems it is difficult to generate equations which are to be optimized. Such problems can be optimized by using Design Optimization in ANSYS. But in many cases, it ...

With a global search mechanism, particle swarm optimization (PSO) has shown promise in feature selection (FS). However, most of the current PSO-based FS methods use a fix-length representation, which ...

Particle swarm optimization (PSO) algorithm, which is an intelligent optimization algorithm, has many characteristics such as simple structure, less parameter, easy description and realization, strong ...