|A number of techniques have been introduced to construct fuzzy models from measured data. Most attention has been focused on multiple-input, single-output (MISO) systems. This article concentrates on the identi cation of multiple-input, multiple-output (MIMO) systems by means of product-space fuzzy clustering with adaptive distance measure (the Gustafson-Kessel algorithm). The MIMOmodel is rep...

The color reduction in digital images is an active research area in digital image processing. In many applications such as image segmentation, analysis, compression and transmission, it is preferable to have images with a limited number of colors. In this paper, a color clustering technique which is a combination of a Kohonen Self Organized Featured Map (KSOFM) and a fuzzy clustering algorithm ...

Methods for supervised and unsupervised clustering and machine learning were studied in order to automatically model relationships between gene expression data and gene functions of the microorganism Escherichia coli. From a pre-selected subset of 265 genes (belonging to 3 functional groups) the function has been predicted with an accuracy of 63-71 % by various data mining methods described in ...

This paper simulates four typical defects in GIS for PD detection, and uses the pulse, amplitude, phase and number of PD to form the three-dimensional PQN matrix. Based on the PQN, three two-dimensional distributions of Hqmax~Phi, Hqmean~Phi and Hn~Phi can be achieved. Then the new G-K clustering method is introduced to separate the four different defects according to the parameters of Sk, Ku, ...

1.1. Problem definition: Neuro-Fuzzy Approach in Electrical Load Forecasting Modeling and identification of electrical load processes are essential for the operation and also planning of a utility either for a company or for a country. Electrical load forecasting is needed because people intend to make important decision on generating power generators, load switching, purchasing strategy and al...

Electric arc furnaces (EAFs) are intended for the recycling of steel scrap. One more important variables in process is tapping temperature steel. Due to nature process, continuous measurement melt complicated and requires sophisticated measuring equipment; therefore, most EAFs, separate samples taken several times before tapped, verify whether within prescribed range. The measurements obtained ...

Bearing in mind that lack of data is a common problem in the study of porphyry copper mining exploration, our goal was set to identify the hidden patterns within the data and to extend the information to the data-less areas. To do this, the combination of pattern recognition techniques has been used. In this work, multi-layer neural network was used to estimate the concentration of geochemical ...

This article studies the fuzzy cluster-based point set registration (FuzzyPSReg). First, we propose a new metric based on Gustafson–Kessel (GK) clustering to measure alignment of two clouds. Unlike c-means (FCM) in our previous work, GK-based includes orientation properties clouds, thereby providing more information for registration. We then develop quality assessment metric, which is sensitive...

Three-dimensional (3D) image reconstruction of tumours can visualise their structures with precision and high resolution. In this article, GAN-LSTM-3D method is proposed for 3D lung cancer from 2D CT images. Our consists three phases: segmentation, tumour reconstruction. Lung segmentation done using snake optimisation followed by Gustafson-Kessel (GK) clustering method. The outputs GK (2D image...