APPLICATION OF A PROBABILISTIC NEURAL NETWORK FOR LIQUEFACTION ASSESSMENT
نویسندگان
چکیده
منابع مشابه
LIQUEFACTION POTENTIAL ASSESSMENT USING MULTILAYER ARTIFICIAL NEURAL NETWORK
In this study, a low-cost, rapid and qualitative evaluation procedure is presented using dynamic pattern recognition analysis to assess liquefaction potential which is useful in the planning, zoning, general hazard assessment, and delineation of areas, Dynamic pattern recognition using neural networks is generally considered to be an effective tool for assessing of hazard potential on the b...
متن کاملassessment of the efficiency of s.p.g.c refineries using network dea
data envelopment analysis (dea) is a powerful tool for measuring relative efficiency of organizational units referred to as decision making units (dmus). in most cases dmus have network structures with internal linking activities. traditional dea models, however, consider dmus as black boxes with no regard to their linking activities and therefore do not provide decision makers with the reasons...
liquefaction potential assessment using multilayer artificial neural network
in this study, a low-cost, rapid and qualitative evaluation procedure is presented using dynamic pattern recognition analysis to assess liquefaction potential which is useful in the planning, zoning, general hazard assessment, and delineation of areas, dynamic pattern recognition using neural networks is generally considered to be an effective tool for assessing of hazard potential on the basis...
متن کاملStatic Security Assessment Using a Probabilistic Neural Network Based Classifier
In this paper, a probabilistic neural network (PNN) based classifier is used to judge the static security of the power system. The proposed classifier classifies the security of the power system based on the voltage profile of each bus in reference to changes in the generation and load profile in the system. The probabilistic neural network is used and compared with the radial basis function ne...
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: Neural Network World
سال: 2017
ISSN: 1210-0552,2336-4335
DOI: 10.14311/nnw.2017.27.030