Since deep neural networks were developed, they have made huge contributions to
everyday lives. Machine learning provides more rational advice than humans are capable of …

From the past few decades many nature inspired algorithms have been developed and
gaining more popularity because of their effectiveness in solving problems of distinct …

Recent interest in complex and computationally expensive machine learning models with
many hyperparameters, such as automated machine learning (AutoML) frameworks and …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

This paper focuses on the engineering and computer science aspects of developments,
applications, and resources related to particle swarm optimization. Developments in the …

We empirically study the performance of the particle swarm optimizer (PSO). Four different
benchmark functions with asymmetric initial range settings are selected as testing functions …

This paper presents a new algorithm named spherical vector-based particle swarm
optimization (SPSO) to deal with the problem of path planning for unmanned aerial vehicles …

This paper introduces a novel parameter automation strategy for the particle swarm
algorithm and two further extensions to improve its performance after a predefined number …

This is the first book devoted entirely to Particle Swarm Optimization (PSO), which is a non-
specific algorithm, similar to evolutionary algorithms, such as taboo search and ant colonies …

One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …