This paper analyses a multi-compressor system for its performance failures and subsequent improvements. The logbook data of this system has been obtained. Data has been classified using various state-of-art data classification techniques. This paper presents a comparative analysis of Fuzzy clustering algorithm, Hard-c-means clustering and Gustafson-Kessel clustering algorithm. Data clustering e...

Image segmentation refers to the technology to segment the image into different regions with different characteristics and to extract useful objectives, and it is a key step from image processing to image analysis. Based on the comprehensive study of image segmentation technology, this paper analyzes the advantages and disadvantages of the existing fuzzy clustering algorithms; integrates the pa...

Data mining technology has emerged as a means for identifying patterns and trends from large quantities of data. Data mining is a computational intelligence discipline that contributes tools for data analysis, discovery of new knowledge, and autonomous decision making. Clustering is a primary data description method in data mining which group’s most similar data. The data clustering is an impor...

Recently, the location of the fingerprint positioning technology is obviously superior to the signal transmission loss model based on the positioning technology, and is widely concerned by scholars. In the online phase, due to the efficiency of the probabilistic distribution matching computation is low and when clustering the position fingerprint database, hard clustering lead to degrading the ...

Formal concept analysis (FCA) is a branch of applied mathematics with roots in lattice theory (Wille, 1982; Ganter & Wille, 1999). It deals with the notion of a concept in a given universe, which it calls context. For example, consider the context of transactions at a grocery store where each transaction consists of the items bought together. A concept here is a pair of two sets (A, B). A is th...

During the recent past, FCA has received significant attention from the research communities of various fields. Further, the theory of FCA is being extended into different frontiers and being augmented with other knowledge representation frameworks. In this backdrop, this paper aim to provide an understanding on necessary mathematical background for each extension of FCA like FCA with granular ...

In this paper, the intelligent techniques are applied to enhance the quality control precision in the steel strip cold rolling production. Firstly a new control scheme is proposed, establishing the classifier of the steel strip cross-sectional 358 Ch. Tang, Sh. Wang, Y. Chen profiles is the core of the system. The fuzzy clustering algorithm is used to establish the classifier. Secondly, a novel...

Researchers have observed that multistage clustering can accelerate convergence and improve clustering quality. Two-stage and two-phase fuzzy C-means (FCM) algorithms have been reported. In this paper, we demonstrate that the FCM clustering algorithm can be improved by the use of static and dynamic single-pass incremental FCM procedures. Keywords-Clustering; Fuzzy C-Means Clustering; Incrementa...

Effective image segmentation cannot be achieved for a fuzzy clustering algorithm based on using only pixel intensity, pixel locations or a combination of the two. Often if both pixel intensity and pixel location are combined, one feature tends to minimize the effect of other, thus degrading the resulting segmentation. This paper directly addresses this problem by introducing a new algorithm cal...

As one of the most popular and well-recognized clustering methods, fuzzy C-means (FCM) clustering algorithm is the basis of other fuzzy clustering analysis methods in theory and application respects. However, FCM algorithm is essentially a local search optimization algorithm. Therefore, sometimes, it may fail to find the global optimum. For the purpose of getting over the disadvantages of FCM a...