In supervised learning, a training set consisting of labeled instances is used by a learning algorithm for generating a model (classifier) that is subsequently employed for decidi...
This paper deals with the adaptive variance scaling issue in continuous Estimation of Distribution Algorithms. A phenomenon is discovered that current adaptive variance scaling me...
Exploratory testing (ET) – simultaneous learning, test design, and test execution – is an applied practice in industry but lacks research. We present the current knowledge of ...
In this work, Self Organizing Map (SOM) is used in order to classify the types of defections in electrical systems, known as Power Quality (PQ) events. The features for classificat...
Implementing and maintaining complicated manufacturing processes in an error-free mode is essential to the survival of any manufacturing business. One essential element to realizi...