Formulation of development strategies for regional agricultural resource potential: The ukrainian case
N Shpak, I Kulyniak, M Gvozd, J Vveinhardt, N Horbal - Resources, 2021 - mdpi.com
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 …
creates the basis for their economic growth. Every region in every country has its own …
Cluster analysis as a tool for improving the performance of agricultural enterprises in the agro-industrial sector
R Huseynov, N Aliyeva, V Bezpalov… - Environment …, 2024 - Springer
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 …
clustering that will allow us to diagnose their market position and identify integration …
Fuzzy ontology datatype learning using Datil
Semantic Web technologies (especially, ontologies) are very important nowadays in
intelligent applications to represent the important knowledge in an application domain …
intelligent applications to represent the important knowledge in an application domain …
Pk-means: k-means using partition based cluster initialization method
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 …
basic k-means, initial cluster centroids are selected on random basis. As a result, every run …
[PDF][PDF] Algorithm for selecting alternative strategiesfor sustainable intensification of agricultural enterprises
SІ Strapchuk, OP Mykolenko - 2022 - researchgate.net
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 …
capacity building. However, this path often leads to a negative impact on the environment …
[PDF][PDF] MP-K-Means: modified partition based cluster initialization method for K-means algorithm
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 …
formation of clusters in each run. Consequently, accuracy and performance of k-means is …
Trends and Advances on The K-Hyperparameter Tuning Techniques in High-Dimensional Space Clustering
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 …
and wealthy history in a variety of disciplines. Application of clustering in computational …
Holonic-C2 Organization Structure Generation Method Based on Clustering Optimization Algorithms
X Wang, J Zhang, L Wan, Z Jiao - IEEE Access, 2019 - ieeexplore.ieee.org
For Holonic-C2 organization-structure generation, a set of methods based on task-cluster
clustering and platform-set optimization are proposed. Initially, the mathematical …
clustering and platform-set optimization are proposed. Initially, the mathematical …
A customer group mining method based on cluster analysis
Y Tang, Z Peng - … and Ubiquitous Engineering: MUE/FutureTech 2019 …, 2020 - Springer
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 …
Taking the tortoise herb jelly WeChat marketing data in WuZhou as an example, how to …
An Efficient Approach for Selection of Initial Cluster Centroids for k-means
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 …
algorithm to group the data objects into various clusters. In basic k-means, pure arbitrary …