Intelligent optimization methods effectively explore and review the response space using
past experiences a population of search agents. These population-based techniques can …

Nature performs complex tasks in a simple yet efficient way. Natural processes may seem
straightforward from outside but are composed of several inherently complicated sub …

This paper considers a new meta-heuristic method called Grey Wolf optimizer (GWO). It is
inspired by the behavior of grey wolves (Canis lupus) in nature, especially the leadership …

This article implements the multi-objective grey wolf optimizer (MOGWO) in the identification
process of a multivariable system. For a sequence of 100 runs, MOGWO approach had …

ABSTRACT HVAC (Heating Ventilating and Air-Conditioning) system is multivariate,
nonlinear, and shares time-varying characteristics. It poses challenges for both system …

Several gradient-based approaches such as back propagation (BP) and Levenberg
Marquardt (LM) methods have been developed for training the neural network (NN) based …

Filtering, or digital signal processing, is a significant and fundamental requirement in fields
such as signal systems and computers. The process of designing optimal digital filters is …

Different soft computing techniques based on artificial intelligence sub-fields such as fuzzy
logic, neural networks, granular computing, and other nature-inspired evolutionary and …

The present study proposes a multi-objective framework for structure selection of nonlinear
systems which are represented by polynomial NARX models. This framework integrates the …

A complex system is made up of multiple related and coupled subsystems. Each subsystem
has its own set of multiple constraints and objectives, and is commonly found in real-world …