Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)
نویسندگان
چکیده
منابع مشابه
Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)
Article history: Received 20 February 2011 Accepted 4 April 2011 Available online xxxx
متن کاملModeling of Weld Bead Geometry Using Adaptive Neuro-Fuzzy Inference System (ANFIS) in Additive Manufacturing
Additive Manufacturing describes the technologies that can produce a physical model out of a computer model with a layer-by-layer production process. Additive Manufacturing technologies, as compared to traditional manufacturing methods, have the high capability of manufacturing the complex components using minimum energy and minimum consumption. These technologies have brought about the possibi...
متن کاملBreast Cancer Risk Assessment Using adaptive neuro-fuzzy inference system (ANFIS) and Subtractive Clustering Algorithm
Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used. First,...
متن کاملNusselt Number Estimation along a Wavy Wall in an Inclined Lid-driven Cavity using Adaptive Neuro-Fuzzy Inference System (ANFIS)
In this study, an adaptive neuro-fuzzy inference system (ANFIS) was developed to determine the Nusselt number (Nu) along a wavy wall in a lid-driven cavity under mixed convection regime. Firstly, the main data set of input/output vectors for training, checking and testing of the ANFIS was prepared based on the numerical results of the lattice Boltzmann method (LBM). Then, the ANFIS was develope...
متن کاملBreast Cancer Risk Assessment Using adaptive neuro-fuzzy inference system (ANFIS) and Subtractive Clustering Algorithm
Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used. First,...
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: Applied Energy
سال: 2011
ISSN: 0306-2619
DOI: 10.1016/j.apenergy.2011.04.015