scholarly journals Soft Computing Models in Industrial and Environmental Applications, 6th International Conference SOCO 2011

2011 ◽  
Keyword(s):  
Soft Computing ◽  
Environmental Applications ◽  
International Conference ◽  
Computing Models

scholarly journals Selected papers from the 6th International Conference on Soft Computing Models in Industrial and Environmental Applications

2012 ◽  
Vol 10 (4) ◽  
pp. 275-276
Author(s):  
Guest Editors ◽  
Emilio Corchado ◽  
Ajith Abraham ◽  
Václav Snášel ◽  
Javier Sedano ◽  
...  
Keyword(s):  
Soft Computing ◽  
Environmental Applications ◽  
International Conference ◽  
Computing Models

scholarly journals New trends on soft computing models in industrial and environmental applications

2013 ◽  
Vol 109 ◽  
pp. 1-2 ◽  
Author(s):  
Emilio Corchado ◽  
Ajith Abraham ◽  
Václav Snášel
Keyword(s):  
Soft Computing ◽  
Environmental Applications ◽  
Computing Models

scholarly journals Applications of soft computing models for predicting sea surface temperature: a comprehensive review and assessment

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Masoud Haghbin ◽  
Ahmad Sharafati ◽  
Davide Motta ◽  
Nadhir Al-Ansari ◽  
Mohamadreza Hosseinian Moghadam Noghani
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Soft Computing ◽  
Sea Surface ◽  
Linear Processes ◽  
Comprehensive Review ◽  
Droughts And Floods ◽  
Input Variables ◽  
And Performance ◽  
Computing Models

AbstractThe application of soft computing (SC) models for predicting environmental variables is widely gaining popularity, because of their capability to describe complex non-linear processes. The sea surface temperature (SST) is a key quantity in the analysis of sea and ocean systems, due to its relation with water quality, organisms, and hydrological events such as droughts and floods. This paper provides a comprehensive review of the SC model applications for estimating SST over the last two decades. Types of model (based on artificial neural networks, fuzzy logic, or other SC techniques), input variables, data sources, and performance indices are discussed. Existing trends of research in this field are identified, and possible directions for future investigation are suggested.

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