In many pattern recognition tasks, an approach based on combining classifiers has shown a significant potential gain in comparison to the performance of an individual best classifier. This improvement turned out to be subject to a sufficient level of diversity exhibited among classifiers, which in general can be assumed as a selective property of classifier subsets. Given a large number of clas...

An appropriate classification of the surface myoelectric signals (MES) allows people with disabilities to control assistive prosthetic devices. The performance of these pattern recognition methods significantly affects the accuracy and smoothness of the target movements. We designed an intelligent Support Vector Machine (SVM) classifier to incorporate potential variations in electrode placement...

Analog electronic circuits play an essential role in many industrial applications and control systems. The traditional way of diagnosing failures such can be inaccurate time-consuming process; therefore, it affect the outcome negatively. In this paper, intelligent fault diagnosis identification approach for analog is proposed investigated. method relies on a simple statistical analysis frequenc...

Abstract In the current era, a tremendous volume of data has been generated by using web technologies. The association between different devices and services have also explored to wisely widely use recent Due restriction in available resources, chance security violation is increasing highly on constrained devices. IoT backend with multi-cloud infrastructure extend public terms better scalabilit...

A generic predator/prey pursuit scenario is used to validate a common learning approach using Wilson’s eXtended Learning Classifier System (XCS). The predators, having only local information, should independently learn and act while at the same time they are urged to collaborate and to capture the prey. Since learning from scratch is often a time consuming process, the common learning approach,...

We compare the purposes, inputs, representations, and assumptions of three methods to evaluate the fine-grained interactions of intelligent tutors with their students. One method is conventional analysis of randomized controlled trials (RCTs). The second method is learning decomposition, which estimates the impact of each practice type as a parameter in an exponential learning curve. The third ...

The goal is to develop a novel approach for cardiac disease prediction and diagnosis using intelligent agents. Initially the symptoms are preprocessed using filter and wrapper based agents. The filter removes the missing or irrelevant symptoms. Wrapper is used to extract the data in the data set according to the threshold limits. Dependency of each symptom is identified using dependency checker...

A single student step in an intelligent tutor may involve multiple subskills. Conventional approaches either sidestep this problem, model the step as using only its least known subskill, or treat the subskills as necessary and probabilistically independent. In contrast, we use logistic regression in a Dynamic Bayes Net (LR-DBN) to trace the multiple subskills. We compare these three types of mo...