This study uses data mining techniques to examine the effect of various demographic, cognitive and psychographic factors on Egyptian citizens’ use of e-government services. Multi-layer perceptron neural network (MLP), probabilistic neural network (PNN), classification and regression trees (CART), and multivariate adaptive regression splines (MARS) are compared to a standard statistical method (...

The planning and management of water resources are affected by streamflow. analysis the sustainability has used well-grounded methods such as artificial neural networks, for streamflow forecasting researchers in recent years. main aim this study is to evaluate performance various long-term from data mean monthly streamflows between 1981 2017 Kucukmuhsine station on Meram Stream Turkish province...

In the present study, an improved adaptive neuro fuzzy inference system (ANFIS) and multilayer perceptron (MLP) models are hybridized with a sunflower optimization (SO) algorithm introduced for lake water level simulation. The Urmia Lake is predicted assessed using potential of proposed advanced artificial intelligence (AI) models. implemented to find optimal tuning parameters. results indicate...

Abstract The purpose of this study is the projection climate change's impact on Groundwater Level (GWL) fluctuations in Mashhad aquifer during future period (2022–2064). In first step, climatic variables using ACCESS-CM2 model under Shared Socio-economic Pathways (SSPs) 5–8.5 scenario were extracted. second different machine learning algorithms, including Multilayer Perceptron Neural Network (M...

A general problem in model selection is to obtain the right parameters that make a model fit observed data. For a Multilayer Perceptron (MLP) trained with Backpropagation (BP), this means finding the right hidden layer size, appropriate initial weights and learning parameters. This paper proposes a method (G-Prop-II) that attempts to solve that problem by combining a genetic algorithm (GA) and ...

In this paper we propose a synergistic melting of neural networks and decision trees (DT) we call neural decision trees (NDT). NDT is an architecture a la decision tree where each splitting node is an independent multilayer perceptron allowing oblique decision functions or arbritrary nonlinear decision function if more than one layer is used. This way, each MLP can be seen as a node of the tree...

A general problem in model selection is to obtain the right parameters that make a model "t observed data. For a multilayer perceptron (MLP) trained with back-propagation (BP), this means "nding appropiate layer size and initial weights. This paper proposes a method (G-Prop, genetic backpropagation) that attempts to solve that problem by combining a genetic algorithm (GA) and BP to train MLPs w...

This paper presents an Intrusion Detection System (IDS) with the integration of multi agent systems and artificial intelligence techniques such as fuzzy logic controller (FLC), multi-layer perceptron (MLP) and adaptive neurofuzzy inference system (ANFIS). The paper introduces Network Intrusion Detection Systems (NIDS), which monitors the network traffic and detect any possible attacks. The syst...