PURPOSE Respiratory motion prediction using an artificial neural network (ANN) was integrated with pseudocontinuous arterial spin labeling (pCASL) MRI to allow free-breathing perfusion measurements in the kidney. In this study, we evaluated the performance of the ANN to accurately predict the location of the kidneys during image acquisition. METHODS A pencil-beam navigator was integrated with...

Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link,...

Long-term measurements of CO(2) flux can be obtained using the eddy covariance technique, but these datasets are affected by gaps which hinder the estimation of robust long-term means and annual ecosystem exchanges. We compare results obtained using three gap-fill techniques: multiple regression (MR), multiple imputation (MI), and artificial neural networks (ANNs), applied to a one-year dataset...

Abstract: This paper discusses short-term electricity-load forecasting using an extreme learning machine (ELM) with automatic knowledge representation from a given input-output data set. For this purpose, we use a Takagi-Sugeno-Kang (TSK)-based ELM to develop a systematic approach to generating if-then rules, while the conventional ELM operates without knowledge information. The TSK-ELM design ...

BACKGROUND We previously proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in forecasting schistosomiasis. Our purpose in the current study was to forecast the annual prevalence of human schistosomiasis in Yangxin County, using our ARIMA-NARNN model, thereby further certifying the reliabilit...

In this study, morphometric features such as total length, standard length, and fork length obtained from a total of 321 Sparus aurata samples, including 164 females and 157 males, captured between 2012 and 2013 from İskenderun Bay were used as input value, while weight was used as an output value. The Artificial Neural Network (MLP-Multi-L Layer Perceptron) as well as the M5P algorithm and Lin...

Predicting the post-blast re-entry time precisely can improve productivity and reduce accidents significantly. The empirical formulas for prediction are practical to implement, but lack accuracy. In this study, a novel method based on back-propagation neural network (BPNN) was proposed tackle drawbacks. A numerical model constructed 300 points of sample data were recorded, with consideration fr...

Emerging wireless sensor networking (WSN) and modern machine learning techniques have encouraged interest in the development of vehicle health monitoring (VHM) systems that ensure secure and reliable operation of the rail vehicle. The performance of rail vehicles running on railway tracks is governed by the dynamic behaviours of railway bogies especially in the cases of lateral instability and ...

a-Si Electronic Portal Imaging Device (EPID) is an important tool to verify the location of the radiation therapy beam with respect to the patient anatomy. But, Electronic Portal Images (EPI) suffer from low contrast. In order to have better in-treatment images to extract relevant features of the anatomy, image processing tools need to be integrated in the Radiology systems. The goal of this re...