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The approach described in this paper represents a substantive departure from the conventional quantitative techniques of system analysis. It has three main distinguishing features: 1) use of so-called ``linguistic'' vari...

1. Introduction. 2. Partitioning Around Medoids (Program PAM). 3. Clustering large Applications (Program CLARA). 4. Fuzzy Analysis. 5. Agglomerative Nesting (Program AGNES). 6. Divisive Analysis (Program DIANA). 7. Monot...

With the shift towards a more sustainable energy system, the need for a better understanding of the behavior development over time of consumers and prosumers arises. Despite the growing penetration of smart meter infrast...

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a l...

E-mail texts are hard to process due to their short length. In this article, the use of a diffuse neural network that is capable of identifying the most relevant terms in a set of e-mails is proposed. The associations be...

Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disci...

Materias / palabras clave: Cluster analysis; Computer science; Correlation clustering; Consensus clustering; CURE data clustering algorithm; Fuzzy clustering; Single-linkage clustering; Conceptual clustering; Artificial intelligence; Clustering hi...

In this Ph. D thesis, the main significant contributions are: formulation of a new non-linear membership function using fuzzy approach to capture and describe vagueness in the technological coefficients of constraints in...