the main objective of this study was to investigate how months cluster in any thermal regions based on temperature. for this purpose, the mean of daily temperature data have been provided using 620 synoptic and climatology stations. then, mean temperature was converted for any station, based on solar calendar, and maps of mean daily temperature have been interpolated using kriging method. spati...

the species of dioscorea (yam) are regarded as a staple food crop for millions of people in the tropical and subtropical regions of the world. it is regarded as an important food crop next to cereals and grains due to high yield storage of carbohydrates. economically, only few species are recognized for cultivation from agricultural point of view, in spite of its large species diversity. the sp...

Over 3 000 Mozambican smallholder farmers supply cassava to Company XYZ. XYZ needs an effective supplier segmentation method gain insight into how it should direct its resources for the greatest impact. This paper describes application of the  k -means algorithm, agglomerative hierarchical clustering, and a self-organising map with ward clustering segment these suppliers. The insights gained fr...

The hierarchy is often used to infer knowledge from groups of items and relations in varying granularities. Hierarchical clustering algorithms take an input of pairwise data-item similarities and output a hierarchy of the data-items. This paper presents Bidirectional agglomerative hierarchical clustering to create a hierarchy bottom-up, by iteratively merging the closest pair of data-items into...

A hierarchical agglomerative clustering algorithm based on the analysis of dissimilarity increments between neighboring patterns is presented. The first derivative of dissimilarity between neighboring patterns inside a natural cluster is modelled by an exponential distribution, this statistic characterizing the cluster. A cluster isolation criterion is defined based on estimates of each cluster...

spatial distribution of thermal regions is dependent on local factors and circulation patterns in long terms. recognition of spatial distribution of temperature in geographical regions could be help on planning and environmental policies. the aim of this paper is recognition and detachment of thermal regions in iran. for this object, maximum daily temperature data have been provided using 620 s...

To implement divisive hierarchical clustering algorithm with K-means and to apply Agglomerative Hierarchical Clustering on the resultant data in data mining where efficient and accurate result. In Hierarchical Clustering by finding the initial k centroids in a fixed manner instead of randomly choosing them. In which k centroids are chosen by dividing the one dimensional data of a particular clu...

We explore the use of instance and cluster-level constraints with agglomerative hierarchical clustering. Though previous work has illustrated the benefits of using constraints for non-hierarchical clustering, their application to hierarchical clustering is not straight-forward for two primary reasons. First, some constraint combinations make the feasibility problem (Does there exist a single fe...

Symbolic Data Analysis (SDA) aims to to describe and analyze complex and structured data extracted, for example, from large databases. Such data, which can be expressed as concepts, are modeled by symbolic objects described by multivalued variables. In the present paper we present a new distance, based on the Wasserstein metric, in order to cluster a set of data described by distributions with ...