کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6963831 | 1452293 | 2014 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Analysing coastal ocean model outputs using competitive-learning pattern recognition techniques
ترجمه فارسی عنوان
تجزیه و تحلیل خروجی مدل اقیانوس ساحل با استفاده از تکنیک های تشخیص الگو های رقابتی
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کلمات کلیدی
تشخیص الگو، نقشه های خودمراقبتی، مدل سازی اقیانوس، داده کاوی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزار
چکیده انگلیسی
To assist in interpreting the hydrodynamics of a complex coastal environment, a Self Organizing Map (SOM) has been constructed using output from a three-dimensional hydrodynamic model of the Huon-D'Entrecasteaux region in South-East Tasmania, over a one-year period. Interpretation of the SOM enabled nine characteristic or prototype states to be identified. As expected, the dominant forcing mechanisms were freshwater input via riverine discharge and input from oceanic waters. While these mechanisms are well understood, subtle features associated with the interaction of the two forcing mechanisms and the transitions between meta-stable states, were revealed by visualizing the SOM output. Further investigation was undertaken to determine how effective the SOM would be in identifying these prototype states given sensor data from a sensor network being designed for future deployment within the region. This research has demonstrated that SOM analysis can be a useful tool for identifying and interpreting patterns in large oceanographic datasets.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Environmental Modelling & Software - Volume 57, July 2014, Pages 165-176
Journal: Environmental Modelling & Software - Volume 57, July 2014, Pages 165-176
نویسندگان
Raymond N. Williams, Paulo A. Jr., Emlyn M. Jones,