Artificial Neural Networks as Emerging Tools for Earthquake Detection
نویسندگان
چکیده
منابع مشابه
Artificial Neural Networks for Earthquake Anomaly Detection
Earthquakes are natural disasters caused by an unexpected release of seismic energy from extreme levels of stress within the earth’s crust. Over the years, earthquake prediction has been a controversial research subject that has challenged even the smartest of minds. Because numerous seismic precursors and other factors exist that may indicate the potential of an earthquake occurring, it is ext...
متن کاملHYBRID ARTIFICIAL NEURAL NETWORKS BASED ON ACO-RPROP FOR GENERATING MULTIPLE SPECTRUM-COMPATIBLE ARTIFICIAL EARTHQUAKE RECORDS FOR SPECIFIED SITE GEOLOGY
The main objective of this paper is to use ant optimized neural networks to generate artificial earthquake records. In this regard, training accelerograms selected according to the site geology of recorder station and Wavelet Packet Transform (WPT) used to decompose these records. Then Artificial Neural Networks (ANN) optimized with Ant Colony Optimization and resilient Backpropagation algorith...
متن کاملArtificial neural networks as prediction tools in the critically ill
The past 25 years have witnessed the development of improved tools with which to predict short-term and long-term outcomes after critical illness. The general paradigm for constructing the best known tools has been the logistic regression model. Recently, a variety of alternative tools, such as artificial neural networks, have been proposed, with claims of improved performance over more traditi...
متن کاملArtificial Neural Networks as Statistical Tools in SAR/QSAR Modeling
There are two broadly-defined applications of artificial neural networks (ANNs) in SAR/QSAR modeling. The first is the use of networks as preprocessors to reduce the dimensionality of chemical descriptors for use in statistical or network models. The second is to create classification models for predictive toxicology. This report discusses the use of ANNs as classifiers in SAR/QSAR modeling and...
متن کاملArtificial Neural Networks for Misuse Detection
Misuse detection is the process of attempting to identify instances of network attacks by comparing current activity against the expected actions of an intruder. Most current approaches to misuse detection involve the use of rule-based expert systems to identify indications of known attacks. However, these techniques are less successful in identifying attacks which vary from expected patterns. ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computación y Sistemas
سال: 2019
ISSN: 2007-9737,1405-5546
DOI: 10.13053/cys-23-2-3197