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...

This paper describes how patterns of industrial clustering arise with respect to the size of an initial firm whenmeasured in terms of innovation. Through principles of evolutionary economics, the aim of this paper is to examine the ’birth’ of industrial clusters. We take an endogenous and supply-side approach, where firms in a region spawn from incumbents. Technology is qualitatively described ...

This short extract is part of a wider study into the use of the web for research into the presence and structure of industrial clusters and is concerned here with the discernment of networks of firms and the presence of commonalities of competence amongst firms within the identified networks. The research shows that the information that can be extracted using web based methods is sufficiently i...

There are many clustering methods, such as hierarchical clustering method. Most of the approaches to the clustering of variables encountered in the literature are of hierarchical type. The great majority of hierarchical approaches to the clustering of variables are of agglomerative nature. The agglomerative hierarchical approach to clustering starts with each observation as its own cluster and ...

The self-organizing map (SOM) has been widely used in many industrial applications. Classical clustering methods based on the SOM often fail to deliver satisfactory results, specially when clusters have arbitrary shapes. In this paper, through some preprocessing techniques for 4ltering out noises and outliers, we propose a new two-level SOM-based clustering algorithm using a clustering validity...

The objective of the present work is to develop a novel approach for combining in an ensemble multiple base clusterings of operational transients of industrial equipment, when the number of clusters in the final consensus clustering is unknown. A measure of pairwise similarity is used to quantify the co-association matrix that describes the similarity among the different base clusterings. Then,...

The paper integrates two important areas of literature, the Chandler model of corporate hierarchy and the discrete alternative models of small firm flexible specialization, in order to explore long-run processes of structural and strategic change. To achieve synthesis, resource based view (RBV) and resource dependency theories are combined to explain the evolution of different industry structur...

Understanding of energy consumption patterns is extremely important for optimization of resources and application of green trends. Traditionally, analyses were performed for large environments like regions and nations. However, with the advent of Smart Grids, the study of the behavior of smaller environments has become a necessity to allow a deeper micromanagement of the energy grid. This paper...

In this paper a Pattern Recognition algorithm based on a constrained version of the k-means clustering algorithm will be presented. The proposed algorithm is a non parametric supervised statistical pattern recognition algorithm, i.e. it works under very mild assumptions on the dataset. The performance of the algorithm will be tested, togheter with a feature extraction technique that captures th...