Nature inspired algorithms have become popular for discovering classification rules due to
their ability to effectively handle large and complex search spaces. However, nature inspired …

The problem of assessment, selection and improvement of key performance indicators in the
New Service Development process is one of the most important tasks of process managers …

Understanding consumer behavior is beneficial to a business in various aspects such as
prediction of manufacturing quantity, new product launch, and aids in lock-in customers and …

This paper proposes a novel classification model called sparse fuzzy classifier (SFC), which
uses a sparse Takagi-Sugeno fuzzy system to classify data. This system is considered with …

The temperature control of glass tempering and annealing process has the problems of the
time varying parameters and time lag characteristic. In order to solve this problem, this paper …

Decision trees are the most admired and extensively used classification algorithms in data
mining. These are considered accurate, easy to use, and comprehensible classifiers. Like …

Most of the classification algorithms discover flat Fuzzy Classification Rules (FCRs) in 'If-
Then'form. The knowledge discovered in the form of FCRs allows us to deal with vague …

Adding fuzziness to normal classification rules enables the rules to adapt to the real-life
decision-making process. Besides, it also adds to the classification accuracy of the obtained …

Now a days, searching of specific type of knowledge from the usual standards is very useful
in several domains such as medical diagnosis, fraud detection, network traffic anomalies …