The agricultural sector is one of the leading ones in the economy of many countries, as it
creates the basis for their economic growth. Every region in every country has its own …

The objective of this study is to develop a comprehensive approach to agricultural enterprise
clustering that will allow us to diagnose their market position and identify integration …

Semantic Web technologies (especially, ontologies) are very important nowadays in
intelligent applications to represent the important knowledge in an application domain …

The k-Means algorithm is extensively used in a number of data clustering applications. In
basic k-means, initial cluster centroids are selected on random basis. As a result, every run …

Growing food shortage encourage businesses to increase yields, mainly through extensive
capacity building. However, this path often leads to a negative impact on the environment …

In k-means algorithm, initial cluster centroids are selected arbitrarily which leads to diverse
formation of clusters in each run. Consequently, accuracy and performance of k-means is …

Clustering is one of the tasks performed during exploratory data analysis with an extensive
and wealthy history in a variety of disciplines. Application of clustering in computational …

For Holonic-C2 organization-structure generation, a set of methods based on task-cluster
clustering and platform-set optimization are proposed. Initially, the mathematical …

With the rapid development of WeChat's business economy, customer data is exploding.
Taking the tortoise herb jelly WeChat marketing data in WuZhou as an example, how to …

Choice of initial centroids has a major impact on the performance and accuracy of k-means
algorithm to group the data objects into various clusters. In basic k-means, pure arbitrary …