a field experiment was conducted to study the physical properties of maize grain in response to different urea fertilization methods (urea foliar spraying and soil application), three harvest times (grain moisture content of 20, 30 and 40 pecent) in four maize hybrids (three foreign hybrids e.g. ns640, jeta600 , konsur580 and one common hybrid, sc704 as control) at khorram abad agricultural res...

We present XEM, an eXplainable-by-design Ensemble method for Multivariate time series classification. XEM relies on a new hybrid ensemble that combines explicit boosting-bagging approach to handle the bias-variance trade-off faced by machine learning models and implicit divide-and-conquer individualize classifier errors different parts of training data. Our evaluation shows outperforms state-of...

an Artificial Neural Network classifier is a nonparametric classifier. It does not need any priori knowledge regarding the statistical distribution of the class in a giver selected data Source. While, neural network can be trained to distinguish the criteria used to classify easily in a generalized manner that allows successful classification the newly arrived inputs not used during training. T...

Multiple classification systems play an important role in increasing recognition performance, especially when using heterogeneous classifiers that effectively improve performance. In this study, a new hybrid classifier was designed Fisherface and discriminative common vector approach (DCVA) subspace methods, which gave successful results face recognition. While the process of DCVA is based on p...

brain mr images tissue segmentation is one of the most important parts of the clinical diagnostic tools. pixel classification methods have been frequently used in the image segmentation with two supervised and unsupervised approaches up to now. supervised segmentation methods lead to high accuracy but they need a large amount of labeled data, which is hard, expensive and slow to obtain. moreove...

The primary concern of the rating policies for a banking industry is to develop a more objective, accurate and competitive scoring model to avoid losses from potential bad debt. This study proposes an artificial immune classifier based on the artificial immune network (named AINE-based classifier) to evaluate the applicants’ credit scores. Two experimental credit datasets are used to show the a...

Background: Multiple Sclerosis (MS) is the most frequent non-traumatic neurological disease capable of causing disability in young adults. Detection of MS lesions with magnetic resonance imaging (MRI) is the most common technique. However, manual interpretation of vast amounts of data is often tedious and error-prone. Furthermore, changes in lesions are often subtle and extremely unrepresentati...

Classifying network flows into applications is a fundamental requirement for network administrators. Administrators used to classify network applications by examining transport layer port numbers or application level signatures. However, emerging network applications often send encrypted traffic with randomized port numbers. This makes it challenging to detect and manage network applications. I...

The paper presents a hybrid fuzzy classifier for effective land use land cover mapping. It discusses a Bayesian way of incorporating spatial contextual information into the Fuzzy Noise Classifier (FNC). The FNC was chosen, as it detects noise using spectral information more efficiently than its fuzzy counterparts. The spatial information at the level of second order pixel neighbourhood was mode...

When the data mining procedures deals with the extraction of interesting knowledge from web logs is known as Web usage mining. The result of any mining is successful, only if the dataset under consideration is well preprocessed. One of the important preprocessing steps is handling of null/missing values. Handlings of null values have been a great bit of test for researcher. Various methods are ...