In the present study Artificial Neural Network (ANN) has been optimized using a hybrid algorithm of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The hybrid GA-PSO algorithm has been used to improve the estimation of electricity demand of the state of Tamil Nadu in India. The ANN-GA-PSO model uses gross domestic product (GSDP); electricity consumption per capita; income growth r...

A main criterion for the accuracy of solutions of an Artiicial Neural Network (ANN) for classiica-tion tasks is the architecture. In order to nd problem-adapted topologies of ANNs, we adopted the evolutionary approach to ANN design by employing a Genetic Algorithm (GA) to evolve ANNs which are represented using a direct encoding method. As ANNs of low complexity show better generalization capab...

Abstract In a flood-prone region, quick and accurate flood forecasting is imperative. It can extend the lead time for issuing disaster warnings and allow sufficient time for habitants in hazardous areas to take appropriate action, such as evacuation. In this paper, two hybrid models based on recent artificial intelligence technology, namely, genetic algorithm-based artificial neural network (AN...

Security of networks is the most important challenge of the Internet of Things (IoT) that need smarter security mechanisms. Therefore, a tamper detection (TD) is an efficient security mechanism based on networks of IoT for healthcare applications, which used to deal with security violations. In this paper, a new TD mechanism based IoT for real data of healthcare application called (IOTTD) model...

BACKGROUND This study aims to improve accuracy of Bioelectrical Impedance Analysis (BIA) prediction equations for estimating fat free mass (FFM) of the elderly by using non-linear Back Propagation Artificial Neural Network (BP-ANN) model and to compare the predictive accuracy with the linear regression model by using energy dual X-ray absorptiometry (DXA) as reference method. METHODS A total ...

Various models have been developed over the past several decades to predict the dynamic modulus /E*/ of hot-mix asphalt (HMA) based on regression analysis of laboratory measurements. The models most widely used in the asphalt community today are the Witczak 1999 and 2006 predictive models. Although the overall predictive accuracies for these existing models as reported by their developers are q...

Modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. Recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. Thisstudy made us of adaptive neuro-fuzzy ...