Carbon Monoxide Concentration Forecasting Using ' Hybrid Radial Basis Function Network

Neural network has been renown for its applications in many fields of research especially related to pattern recognition. In this paper, Hybrid Radial Basis Function (HRBF) Neural Network will be exploited to carry out the Carbon Monoxide forecasting. This research utilized the past Carbon Monoxide data to forecast Carbon Monoxide concentrations for several "hours in advance. Instead of performing the off-line forecasting technique, this r..esearch tries to forecast the Carbon Monoxide concentrations by on-line technique. To establish this requirement. the HRBF network is trained by using Adaptive Fuzzy C-Means Clustering Algorithm and Exponential Weighted Recursive Least Square Algorithm. For evaluation purpose, we lise Carbon Monoxide concentration time series from three air quality monitoring stations situated at Sekolah Menenga