Design of an Emergency Prediction and Prevention Platform for Societal Security Decision Support Using Neural Networks

2006 ◽  
pp. 173-174 ◽  
Author(s):  
Zeng-Guang Hou ◽  
Min Tan
Keyword(s):  
Neural Networks ◽  
Decision Support ◽  
Prediction And Prevention

scholarly journals Using extended siamese networks to provide decision support in aquaculture operations

2021 ◽  
Author(s):  
Bjørn Magnus Mathisen ◽  
Kerstin Bach ◽  
Agnar Aamodt
Keyword(s):  
Neural Networks ◽  
Decision Support ◽  
Similar Case ◽  
Decision Makers ◽  
Similarity Function ◽  
Case Based Reasoning ◽  
Similarity Learning ◽  
Reasoning System ◽  
Siamese Networks ◽  
Case Based

AbstractAquaculture as an industry is quickly expanding. As a result, new aquaculture sites are being established at more exposed locations previously deemed unfit because they are more difficult and resource demanding to safely operate than are traditional sites. To help the industry deal with these challenges, we have developed a decision support system to support decision makers in establishing better plans and make decisions that facilitate operating these sites in an optimal manner. We propose a case-based reasoning system called aquaculture case-based reasoning (AQCBR), which is able to predict the success of an aquaculture operation at a specific site, based on previously applied and recorded cases. In particular, AQCBR is trained to learn a similarity function between recorded operational situations/cases and use the most similar case to provide explanation-by-example information for its predictions. The novelty of AQCBR is that it uses extended Siamese neural networks to learn the similarity between cases. Our extensive experimental evaluation shows that extended Siamese neural networks outperform state-of-the-art methods for similarity learning in this task, demonstrating the effectiveness and the feasibility of our approach.

scholarly journals Intelligent medical systems in diagnosing and treating inflammatory diseases of the pancreas (systematic review)

2018 ◽  
Vol 39 (1) ◽  
pp. 10-15
Author(s):  
A. A. Litvin
Keyword(s):  
Systematic Review ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Inflammatory Diseases ◽  
Review Of The Literature ◽  
Medical Systems ◽  
Pancreatic Diseases

This paper is a systematic review of the literature on the use of intelligent medical systems in the diagnosis and treatment of acute inflammatory pancreatic diseases. The author provides modern literature data on the efficacy of decision support systems based on artificial neural networks to determine the severity, diagnosis and outcome prognosis of pancreatitis and complications.

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