Recent Trends in Artificial Neural Networks - from Training to Prediction

2020 ◽  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Recent Trends ◽  
Artificial Neural

Artificial Neural Networks in Medicine

2021 ◽  
pp. 1901-1918
Author(s):  
Steven Walczak
Keyword(s):  
Neural Networks ◽  
Resource Allocation ◽  
Artificial Neural Networks ◽  
Cost Reduction ◽  
Decision Problems ◽  
The Future ◽  
Recent Trends ◽  
Artificial Neural ◽  
Medical Domain ◽  
Future Direction

Artificial neural networks (ANNs) have proven to be efficacious for modeling decision problems in medicine, including diagnosis, prognosis, resource allocation, and cost reduction problems. Research using ANNs to solve medical domain problems has been increasing regularly and is continuing to grow dramatically. This chapter examines recent trends and advances in ANNs and provides references to a large portion of recent research, as well as looking at the future direction of research for ANN in medicine.

Artificial Neural Networks in Medicine

2022 ◽  
pp. 1491-1509
Author(s):  
Steven Walczak
Keyword(s):  
Neural Networks ◽  
Resource Allocation ◽  
Artificial Neural Networks ◽  
Cost Reduction ◽  
Decision Problems ◽  
The Future ◽  
Recent Trends ◽  
Artificial Neural ◽  
Medical Domain ◽  
Future Direction

Artificial neural networks (ANNs) have proven to be efficacious for modeling decision problems in medicine, including diagnosis, prognosis, resource allocation, and cost reduction problems. Research using ANNs to solve medical domain problems has been increasing regularly and is continuing to grow dramatically. This chapter examines recent trends and advances in ANNs and provides references to a large portion of recent research, as well as looking at the future direction of research for ANN in medicine.

Artificial Neural Networks for Earthquake Anomaly Detection

2014 ◽  
Vol 18 (5) ◽  
pp. 701-713 ◽  
Author(s):  
Aditya Sriram ◽  
◽  
Shahryar Rahanamayan ◽  
Farid Bourennani
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Seismic Event ◽  
Seismic Energy ◽  
Research Subject ◽  
Abnormality Detection ◽  
Seismic Precursors ◽  
Recent Trends ◽  
Artificial Neural ◽  
Precautionary Measures

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 ofminds. Because numerous seismic precursors and other factors exist that may indicate the potential of an earthquake occurring, it is extremely difficult to predict the exact time, location, and magnitude of an impending quake. Nevertheless, evaluating a combination of these precursors through advances in Artificial Intelligence (AI) can certainly increase the possibility of predicting an earthquake. The sole purpose for predicting a seismic event at a pre-determined locality is to provide substantial time for the citizens to take precautionary measures. With this in mind, Artificial Neural Networks (ANNs) have been promising techniques for the detection and prediction of locally impending earthquakes based on valid seismic information. To highlight the recent trends in earthquake abnormality detection, including various ideas and applications, in the field of Neural Networks, valid papers related to ANNs are reviewed and presented herein.

Determination of S-N curves with the application of artificial neural networks

1999 ◽  
Vol 22 (8) ◽  
pp. 723-728 ◽  
Author(s):  
Artymiak ◽  
Bukowski ◽  
Feliks ◽  
Narberhaus ◽  
Zenner
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Artificial Neural
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