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, logistics is what enables the goods to move through distribution and to the end consumer. This is what motivates the researchers … to examine the logistics portion of the supply chain and attempt to determine the relationship between various market … forces and their impact on the cost of logistics. This will be accomplished with transformative analytics techniques, such as …
Persistent link: https://www.econbiz.de/10012043331
collaboration (e-collaboration) has made a presence in the supply chain of international trade. The logistics industry, in …
Persistent link: https://www.econbiz.de/10012048793
authors propose a Mobility Aware Clustering Scheme (MACS), which organizes the IoT devices in clusters using a fitness …
Persistent link: https://www.econbiz.de/10012042684
one, this technique was designed to solve combinatorial optimization problems, and by embedding a clustering algorithm …
Persistent link: https://www.econbiz.de/10012042726
The main goal of this paper is to compare the motif information extracted from clusters and biclusters of the protein using Motif Comparator. The clusters and biclusters are obtained using the PSO k-means algorithm. The functions of the proteins are preferably found from their motif information....
Persistent link: https://www.econbiz.de/10012042934
Clustering is the process of analyzing data to find clusters of data objects that are similar in some sense to one … another. Some research studies have also extended the usage of clustering concept in inventory management. Yet, not many … research studies have considered the application of clustering approach on determining both optimal order quantity and loss …
Persistent link: https://www.econbiz.de/10012042992
introduces a new hierarchical semi-supervised clustering method based on ordinal density. The results of carried out experiments …
Persistent link: https://www.econbiz.de/10012043208
is based mostly on three cluster techniques like; K means, Fuzzy c-means and hierarchical clustering. The authors used … evolutionary techniques like genetic algorithms (GA) to extend the performance of the clustering model. The performance of these … obtained by the K-means clustering technique, 96.50%; whereas, Fuzzy C-means clustering received 93.50% and hierarchical …
Persistent link: https://www.econbiz.de/10012043858
data analysis and predictive modeling of information systems. Firstly, they apply clustering to study the information …
Persistent link: https://www.econbiz.de/10012044227
Clustering is fundamental for using big data. However, AP (affinity propagation) is not good at non-convex datasets …, and the input parameter has a marked impact on DBSCAN (density-based spatial clustering of applications with noise … obtains a group of normalized density from the AP clustering. The estimated parameters are monotonically. Then, the density is …
Persistent link: https://www.econbiz.de/10012044228