Fuzzy C-Means (FCM) and hard clustering are the most common tools for data partitioning. However, the presence of noisy observations in the data may cause generation of completely unreliable partitions from these clustering algorithms. Also, application of the Euclidean distance in FCM only produces spherical clusters. In this paper, a new noise-rejection clustering algorithm based on Mahalanob...

The paper presents a modified structure of Takaga-Sugeno-Kang (TSK) network with a fully automated building and learning algorithm. The modification has resulted in a great reduction of nonlinear parameters of the network (almost three times). The modified network can be initiated using Gustafson-Kessel clustering algorithm. After initiation all parameters are further fine-tuned by an gradient ...

|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, ...

Abstract For the Schrödinger flow from R × R to the 2-sphere S, it is not known if finite energy solutions can blow up in finite time. We study equivariant solutions whose energy is near the energy of the family of equivariant harmonic maps. We prove that such solutions remain close to the harmonic maps until the blow up time (if any), and that they blow up if and only if the length scale of th...

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 ...

Osteoporosis is a worldwide health problem characterized by low bone mineral density and structural deterioration of bone tissue, leading to bone fragility and an increased susceptibility to fractures. Skeletal bone is maintained by the continuous process of bone remodeling by osteoclasts, cells that break down bone, and osteoblasts, cells that rebuild bone. An imbalance between bone resorption...