Nowadays, the development of higher efficient processes and procedures is key for success in industrial environment. The companies have machines, production lines, software hardware tools with high level principles working. Example: Industry 4.0 concept use machines methods near past, upgrade them, gave them new purpose, as a more tool. Some bases those are not which many would think, like grou...

traditional leveraging statistical methods for analyzing today’s large volumes of spatial data have high computational burdens. to eliminate the deficiency, relatively modern data mining techniques have been recently applied in different spatial analysis tasks with the purpose of autonomous knowledge extraction from high-volume spatial data. fortunately, geospatial data is considered a proper s...

of high-quality vegetable and industrial oil. 9 rapd primers, 6 aflp primer combinations and 12 agro-morphological traits were used to assess the genetic diversity of 20 accessions of saf flower representing global germplasm variability. jacquards’ similarity coef ficient were used to understanding the genetic relationships among ccessions, for aflp and rapd markers and euclidian similarity coe...

assigning a set of objects to groups such that objects in one group or cluster are more similar to each other than the other clusters’ objects is the main task of clustering analysis. sspco optimization algorithm is anew optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. one of the things that smart algorithms are applied to solve is the problem ...

Industrial Clusters are regional concentrations of businesses and organizations that compete with each other, complement depend on other. Clustering phenomenon is developing rapidly both in the world Turkey. The reason for this clustering provides significant benefits to sectoral, national competitiveness. In study, it aimed determine cluster actors a potential Kuşadası Marine Tourism Cluster. ...

This paper proposes an Art Modified Single Linkage Clustering approach (ART-MOD-SLC) to solve cell formation problems in Cellular Manufacturing. In this study, an ART1 network is integrated with Modified Single Linkage Clustering (MOD-SLC) to solve cell formation problems. The Percentage of Exceptional Elements (PE), Machine Utilization (MU), Grouping Efficiency (GE) and Grouping Efficacy (GC) ...

Interfacing through the continuously rising amounts of data in technical, medical, scientific, engineering, industrial and monetary fields and their renovation to logical form for the human user is one of the main requirements. To quickly discover and analyze complex patterns and requirements, we need the efficient techniques and need to learn from new data will be necessary for information-int...

Clustering is a fundamental problem in computer science with applications ranging from biology to information retrieval and data compression. In a clustering problem, a set of objects, usually represented as points in a high-dimensional space R, is to be partitioned such that objects in the same group share similar properties. The k-means method is a traditional clustering algorithm, originally...

Fault diagnosis is essential for the reliable, safe, and efficient operation of the plant and for maintaining quality of the products in industrial system. This paper presents an ensemble fault diagnosis algorithm based on fuzzy c-means algorithm (FCM) with the Optimal Number of Clusters (ONC) and probabilistic neural network (PNN), called FCM-ONC-PNN. In clustering methods, the estimation of t...