Incorporating Fuzzy Logic in Harrod’s Economic Growth Model

Incorporating Fuzzy Logic in Data Mining Tasks

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. In this chapter we discuss how fuzzy logic extends the envelop of the main data mining tasks: clustering, classification, regression and association rules. We begin by presenting a formulation of the data mining using fuzzy logic attributes. Then, for each task, we pro...

Incorporating Fuzzy Logic to Reinforcement Learning

The fuzzy logic in air pollution forecasting ‎model

In the paper a model to predict the concentrations of particulate matter PM10, PM2.5, SO2, NO, CO and O3 for a chosen number of hours forward is proposed. The method requires historical data for a large number of points in time, particularly weather forecast data, actual weather data and pollution data. The idea is that by matching forecast data with similar forecast data in the historical data...

Incorporating Fuzzy Logic Admission Control in Simulation Models

Admission Control is of great interest in computer, communication and production network applications. As systems become more complex or need to make decision based on multiple objectives or require to satisfy several constraints, Fuzzy Logic Control (FLC) is a natural tool to handle admission problems. This paper discusses the framework of a tool developed for easily integrating fuzzy logic ad...

Incorporating prior knowledge in fuzzy model identification

This paper presents an algorithm for incorporating a priori knowledge into data-driven identification of dynamic fuzzy models of the Takagi-Sugeno type. Knowledge about the modelled process such as its stability, minimal or maximal static gain, or the settling time of its step response can be translated into inequality constraints on the consequent parameters. By using input-output data, optima...