In logistics operation, delivery times are often uncertain for customers, and accommodating
this uncertainty poses operation challenges as well as extra cost for logistics service …

At present, the DBSCAN clustering algorithm has been commonly used principally due to its
ability in discovering clusters with arbitrary shapes. When the cluster number K is …

Clustering or grouping is among the most important image processing methods that aim to
split an image into different groups. Examining the literature, many clustering algorithms …

Clustering is a complex unsupervised method used to group most similar observations of a
given dataset within the same cluster. To guarantee high efficiency, the clustering process …

The literature has shown that an accurate classification of project stakeholders allows for
more comprehensive planning of their management strategies. The most used classification …

Regarding as an important computing paradigm, cloud computing is to address big and
distributed databases and rather simple computation. In this paradigm, data mining is one of …

Organochlorine pesticides (OCPs), chlorinated hydrocarbon derivatives extensively used in
agriculture and chemical industry, have been banned for several decades in most …

Numerous real-world applications apply categorical data clustering to find hidden patterns in
the data. The K-modes-based algorithm is a popular algorithm for solving common issues in …

The production systems in process industries are confirmed to be tremendously energy-
consuming, and the trust in promoting their energy efficiency has become a concern, with its …

This paper explores the application of machine learning to enhance our understanding of
water accessibility issues in underserved communities called colonias located along the …