Prediction of PM10 concentrations using Fuzzy c-Means and ANN

In this study, the application of one data-driven method, RBFLN, and two knowledge-driven methods (Fuzzy AHP_OWA and fuzzy group decision making) has been

In [14, Theorem 4.2], Fang and Xue set up a fuzzy version of Ascoli theorem which characterized compact subsets of the space C(K, (E 1 , d ∞ )) of all fuzzy-valued continuous

In order to check the perfor- mance of the proposed algorithm, we have compared it against well-known clustering algorithms SC (Spectral Clustering) and [12] and K-means [9], as well

Previously, the authors have proposed a new exploration algorithm based on partitioning unknown space into as many regions as available robots by applying K-Means clustering to

So then, if a malfunction of the system brings about the presence of air in the flow, and ice concentration is measured by means of a Coriolis effect mass flow meter, two

A conditional sampling technique based on a Fuzzy Clustering algorithm has been applied to the analysis of time series of spanwise vorticity fields obtained from time resolved PIV

• Now, we use the fuzzy qualifier to calculate the truth value of

The goal of the pre-processing phase is to extract code snippets from the posted content in the forums, select those using C/C++ language, to extract the functions from these