Classification studies are widely applied, e.g. in biomedical research to classify objects/patients into predefined groups. The goal is to find a classification function/rule which assigns each object/patient to a unique group with the greatest possible accuracy (classification error). Especially in gene expression experiments often a lot of variables (genes) are measured for only few objects/p...

the main purpose of this paper is prediction of tse corporate financial bankruptcy using artificial neural networks. the mean values of key ratios reported in past bankruptcy studies were selected for neural network inputs (working capital to total assets, net income to total assets, total debt to total assets, current assets to current liabilities, quick assets to current liabilities). the neu...

5 L INTRODUCTION 6 2. ARTinCIAL NEURAL NETV/ORKS 8 2.L ANN Models 8 2.2. Introduction to Artificial Neural Networks 8 3. ERROR PREDICTION ON A GENERALIZER 13 3.1. Stacked Generalization 13 3.2. Error Prediction with Cross Validation Partition Criterion (CVPC) 14 3.3. Error Prediction with Bootstrap Partition Criterion (BPC) 17 3.4. Error Prediction with Modified Bootstrap Partition Criterion (M...

this paper presents an accurate differential global positioning system (dgps) using multi-layered neural networks (nns) based on the back propagation (bp) and imperialistic competition algorithm (ica) in order to predict the dgps corrections for accurate positioning. simulation results allowed us to optimize the nn performance in term of residual mean square error. we compare results obtained b...

Prediction of the accurate amount of solid waste is difficult work because several parameters affect it. There is a high degree of fluctuation in the prediction of amount of solid waste generation. Therefore, applying neural network as intelligent system can be a good option. In a tourist area such as Langkawi Island, protection of the area and pollution control are important issues; also it is...

Adaptive interpolation with double-interpolator is used for image coding. The double-interpolator means that two adaptive prediction stages are used. The outer ioop is an adaptive FIRpredictor. The inner ioop is an texture based bias estimation. The bias means a content dependent estimated prediction error. By assuming the signals to consist of polynomials of various degrees, the predictor of t...

We present a decomposition of prediction error for the multilevel model in the context of predicting a future observable y∗j in the jth group of a hierarchical dataset. The multilevel prediction rule is used for prediction and the components of prediction error are estimated via a simulation study that spans the various combinations of level-1 (individual) and level-2 (group) sample sizes and d...

1 Abstract Prediction of atmospheric phenomena needs three components: a theoretical (or numerical) model based on the natural laws (physical, chemical, or biological), a sampling set of the reality, and a tolerance level. Comparison between the predicted and sampled values leads to the estimation of model error. In the error phase space, the prediction error is treated as a point; and the tole...

rainfall is considered a highly valuable climatologic resource, particularly in arid regions. as one of the primaryinputs that drive watershed dynamics, rainfall has been shown to be crucial for accurate distributed hydrologicmodeling. precipitation is known only at certain locations; interpolation procedures are needed to predict this variablein other regions. in this study, the ordinary cokri...

As a kind of traditional Chinese medicinal materials coptis chinensis has a lot of medicinal value and closely related to human health, Widely used in clinical or disease prevention and treatment. So the quality of medicinal coptis chinensis rapid determination is very important. Calibration model for determination of Coptis chinensis’ quality was built by partial least squares and near infrare...