This paper presents the research results of a comparison of three different model based
approaches for wind turbine fault detection in online SCADA data, by applying developed …

In broad terms, there are two approaches to damage identification. Model-driven methods
establish a high-fidelity physical model of the structure, usually by finite element analysis …

The present study was carried out using artificial neural network (ANN) model for predicting
the sodium hazardness, ie, sodium adsorption ratio (SAR), percent sodium (% Na) residual …

This book provides a first synthetic view of an emerging area of ecology and biogeography,
linking individual-and population-level processes to geographic distributions and …

Written by global leaders and pioneers in the field, this book is a must-have read for
researchers, practicing engineers and university faculty working in SHM. Structural Health …

Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …

This volume provides students, researchers and application developers with the knowledge
and tools to get the most out of using neural networks and related data modelling techniques …

Rapid urban and coastal developments often witness deterioration of regional seawater
quality. As part of the management process, it is important to assess the baseline …

This paper proposes a system for wind turbine condition monitoring using Adaptive Neuro-
Fuzzy Interference Systems (ANFIS). For this purpose:(1) ANFIS normal behavior models for …

A modelling framework for studying the combined effects of climate and land‐cover changes
on the distribution of species is presented. The model integrates land‐cover data into a …