This paper presents a taxonomy of explainability in human–agent systems. We consider
fundamental questions about the Why, Who, What, When and How of explainability. First, we …

The metaheuristic genetic algorithm (GA) is based on the natural selection process that falls
under the umbrella category of evolutionary algorithms (EA). Genetic algorithms are typically …

Neural networks and genetic algorithms are the two sophisticated machine learning
techniques presently attracting attention from scientists, engineers, and statisticians, among …

Extreme learning machine (ELM) is a new learning algorithm for the single hidden layer
feedforward neural networks. Compared with the conventional neural network learning …

In the present era, soft computing approaches play a vital role in solving the different kinds of
problems and provide promising solutions. Due to popularity of soft computing approaches …

The determination and classification of a recognized spoken language based on certain
contents and datasets is known as the process of language identification (LID). The common …

This paper proposes a learning framework for single-hidden layer feedforward neural
networks (SLFN) called optimized extreme learning machine (O-ELM). In O-ELM, the …

Genetic algorithm is utilized to design the optimum initial value of parameters and topology
of the artificial neural network which is trained by applying the improved backpropagation …

For next generation aircraft, Adaptive Cycle Engine (ACE) is a candidate to fulfill the multi-
mission requirements of flight. This new concept is promising to complete deficiencies of …

In this work, a novel hybrid neuro‐fuzzy classifier (HNFC) technique is proposed for
producing more accuracy in input data classification. The inputs are fuzzified using a …