Finding compact and well-separated clusters in data sets is a challenging task. Most
clustering algorithms try to minimize certain clustering objective functions. These functions …

Soil attributes and their environmental drivers exhibit different patterns in different
geographical directions, along with distinct regional characteristics, which may have …

Machine learning and pattern recognition both benefit greatly from the study of clustering
techniques. Choosing the right number of clusters in cluster analysis is quite tough. Quality …

Fuzzy C-means clustering (FCM) approach is an effective method for clustering and has
been successfully applied in numbers of real-world problems. In this paper, we propose an …

Abstract The Tinto River is known globally for having a reddish color due to the high
concentration of dissolved metals in its waters. The general objective of this study is to …

The application of clustering has always been an important method for problem-solving. In
the era of big data, most classical clustering methods suffer from the curse of dimensionality …

Globally, hydrographic basins are routinely contaminated by anthropogenic contaminants
originating from coal mining, swine farming, urban sewage, pesticide use, and other various …

Abstract The Amazon River is the longest river in the world. The Tapajós River is a tributary
to the Amazon. At their junction, a marked decrease in water quality is evident from negative …

Abstract Model degradation is still a challenge in real-time applications such as chatbot
systems. This work refers to a webchat service of a Brazilian energy utility company, whose …

While the classical K-means algorithm has been widely used in many fields, it still has some
defects. Therefore, this paper proposes a scheme to improve the clustering quality of K …