Ant colony optimization is a technique for optimization that was introduced in the early
1990's. The inspiring source of ant colony optimization is the foraging behavior of real ant …

This paper focuses on the study of Coronavirus Disease 2019 (COVID-19) X-ray image
segmentation technology. We present a new multilevel image segmentation method based …

Social–ecological systems research suffers from a disconnect between hierarchical (top-
down or bottom-up) and network (peer-to-peer) analyses. The concept of the heterarchy …

A unified view of metaheuristics This book provides a complete background on
metaheuristics and shows readers how to design and implement efficient algorithms to solve …

In this paper we present an extension of ant colony optimization (ACO) to continuous
domains. We show how ACO, which was initially developed to be a metaheuristic for …

Optimization techniques inspired by swarm intelligence have become increasingly popular
during the last decade. They are characterized by a decentralized way of working that …

Purpose–The computational drawbacks of existing numerical methods have forced
researchers to rely on heuristic algorithms. Heuristic methods are powerful in obtaining the …

This article expands on research that has been done to develop a recurrent neural network
(RNN) capable of predicting aircraft engine vibrations using long short-term memory (LSTM) …

The wind is a clean, abundant and entirely renewable source of energy. Large wind farms
are being built around the world as a cleaner way to generate electricity, but operators are …

Ant colony optimization (ACO) is an optimization technique that was inspired by the foraging
behaviour of real ant colonies. Originally, the method was introduced for the application to …