Ecological data are considered to be difficult to analyze because numerous biological and
environmental factors are involved in a complex manner in environment–organism …

The self-organizing map (SOM) is an automatic data-analysis method. It is widely applied to
clustering problems and data exploration in industry, finance, natural sciences, and …

Aims and Scope This book is both an introductory textbook and a research monograph on
modeling the statistical structure of natural images. In very simple terms,“natural images” are …

Kohonen Network - Scholarpedia Kohonen Network From Scholarpedia Teuvo Kohonen
and Timo Honkela (2007), Scholarpedia, 2(1):1568. doi:10.4249/scholarpedia.1568 …

In this study we investigate temporal slowness as a learning principle for receptive fields
using slow feature analysis, a new algorithm to determine functions that extract slowly …

Abstract The Self-Organizing Map (SOM) algorithm has attracted an ever increasing amount
of interest among researches and practitioners in a wide variety of elds. The SOM and a …

Over the past decade the use of machine learning in meteorology has grown rapidly.
Specifically neural networks and deep learning have been used at an unprecedented rate …

Community detection is an important research area in social networks analysis where we
are concerned with discovering the structure of the social network. Detecting communities is …

Publisher Summary This chapter proposes a new type of self-organizing map (SOM) that is
based on discretizations of curved, non-euclidean spaces. As an introductory example, it …

Understanding the characteristics contributing to enhancing flood resilience is a matter of
urgency in managing urban areas, especially for developing countries, given the challenges …