Widespread digitization of information in today’s internet age has intensified the need for effective textual document classification algorithms. Most real life classification problems, including text classification, genetic classification, medical classification, and others, are complex in nature and are characterized by high dimensionality. Current solution strategies include Naïve Bayes (NB)...

Since past few years, researchers have been concentrating on the classification of Electromyography Signal. This method is very useful in diagnosing the neuro-muscular disorders, which consists of wide spread diseases affecting peripheral nervous system. Progressive muscle weakness is the major form of these disorders. Out of various proposed methods, scholars are commonly focusing on Neural Ne...

DOI reference number: 10.18293/SEKE2015-153 Abstract—Recommendation systems are software tools and techniques that provide customized content to users. The collaborative filtering is one of the most prominent approaches in the recommendation area. Among the collaborative algorithms, one of the most popular is the k-Nearest Neighbors (kNN) which is an instance-based learning method. The kNN gene...

The purpose of this work is to present a simple global solar irradiance forecasting framework based on the optimization of the k-nearest-neighbors (kNN) and artificial neural networks algorithms (ANN) for time horizons ranging from 15 min to 2 h. We apply the proposed forecasting models to irradiance from five locations and assessed the impact of different micro-climates on forecasting performa...

We compare four numerical methods for the prediction of missing values in different datasets [1]. These are 1) hierarchical maximum likelihood estimation (ℋ-MLE), and three machine learning (ML) methods, which include 2) k-nearest neighbors (kNN), 3) random forest, 4) Deep Neural Network (DNN). From ML best results (for considered datasets) were obtained by kNN method with (or seven) neighbors....

Abstract The quality of fresh apple fruits is a major concern for consumers and manufacturers. Classification these according to their ripening stage one the most decisive factors in determining quality. In this regard, aim work develop new method non-destructive classification state Fuji apples using hyperspectral information visible near-infrared (Vis/NIR) regions. Spectra 172 samples range f...

In this work, response surface methodology (RSM) and artificial neural network (ANN) were used to predict the decolorization efficiency of Reactive Red 33 (RR 33) by applying the O3/UV process in a bubble column reactor. The effects of four independent variables including time (20-60 min), superficial gas velocity (0.06-0.18 cm/s), initial concentration of dye (50-150 ppm), and pH (3-11) were i...

In this paper, a novel algorithm is developed for identifying Hammerstein model. The static nonlinear function is characterized by function link artificial neural network (FLANN) and the linear dynamic subsystem by an ARMA model. The utilization of FLANN can not only result in a simple and effective representation of static nonlinearity but also simplify the learning algorithm. A two-step proce...

This paper proposes the application of structured neural networks to classification of multisensor remote-sensing images. The purpose of our approach is to allow the interpretation of the “network behavior,” as it can be utilized by photointerpreters for the validation of the neural classifier. In addition, our approach gives a criterion for defining the network architecture, so avoiding the cl...