In this paper dynamic parameter adjustment in particle swarm optimization (PSO) for
modular neural network (MNN) design using granular computing and fuzzy logic (FL) is …

In this paper we propose a fuzzy neural network prediction approach based on
metaheuristics for container flow forecasting. The approach uses fuzzy if–then rules for …

Using a single hidden layer neural network in estimating orientation angles for solar
photovoltaics lacks the complexity required to model nonlinear relationships between input …

In this research work, we propose the model based on the Genetic Algorithm (GA) and Deep
Neural Network (DNN) to enhance the quality and intelligibility of the noisy speech. In this …

Artificial neural networks (ANNs) are one of the most widely used techniques for
generalization, classification, and optimization. ANNs are inspired from the human brain and …

The motivation behind this paper is to explore an algorithm that has the ability to optimize
the free parameters required to design a neural network without being diligent in …

Skin cancer has become the most common form of cancer and most well-known disease of
the human. Early identification of skin cancer is important for improving prognosis, as …

This work plans to design an intelligent Electrocardiogram (ECG) diagnosis support system
that can identify heart abnormalities with high accuracy (ACC), low normalized mean square …

Background To optimize α-amylase synthesis from fermented broth, this research employed
evolutionary and swarm intelligence-based techniques such as genetic algorithm (GA) and …

Background To optimize α-amylase synthesis from fermented broth, this research employed
evolutionary and swarm intelligence-based techniques such as genetic algorithm (GA) and …