Prediction of reservoir brine properties using radial basis function (RBF) neural network
نویسندگان
چکیده
منابع مشابه
Improving Accuracy of DGPS Correction Prediction in Position Domain using Radial Basis Function Neural Network Trained by PSO Algorithm
Differential Global Positioning System (DGPS) provides differential corrections for a GPS receiver in order to improve the navigation solution accuracy. DGPS position signals are accurate, but very slow updates. Improving DGPS corrections prediction accuracy has received considerable attention in past decades. In this research work, the Neural Network (NN) based on the Gaussian Radial Basis Fun...
متن کاملFast Voltage and Power Flow Contingency Ranking Using Enhanced Radial Basis Function Neural Network
Deregulation of power system in recent years has changed static security assessment to the major concerns for which fast and accurate evaluation methodology is needed. Contingencies related to voltage violations and power line overloading have been responsible for power system collapse. This paper presents an enhanced radial basis function neural network (RBFNN) approach for on-line ranking of ...
متن کاملTraining Radial Basis Function Neural Network using Stochastic Fractal Search Algorithm to Classify Sonar Dataset
Radial Basis Function Neural Networks (RBF NNs) are one of the most applicable NNs in the classification of real targets. Despite the use of recursive methods and gradient descent for training RBF NNs, classification improper accuracy, failing to local minimum and low-convergence speed are defects of this type of network. In order to overcome these defects, heuristic and meta-heuristic algorith...
متن کاملImage Reconstruction in X-ray Tomography Using a Radial Basis Function(RBF) Neural Network
Inspection and shape measurement of three-dimensional objects are widely needed in the fields of quality monitoring and reverse engineering. X-ray computed tomography could be a good solution since the method can acquire three dimensional volume information of a product from a series of acquired cross-sectional images. To reconstruct a cross-section in computed tomography, a number of data are ...
متن کاملOptimization of continual production of CNTs by CVD method using Radial Basic Function (RBF) neural network and the Bees Algorithm
Optimization of continuous synthesis of high purity carbon nanotubes (CNTs) using chemical vapour deposition (CVD) method was studied experimentally and theoretically. Iron pentacarbonyl (Fe(CO)5), acetylene (C2H2) and Ar were used as the catalyst source, carbon source and carrier gas respectively. The synthesis temperature and flow rates of Ar and acetylene were optimized to produce CNTs at a ...
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: Petroleum
سال: 2015
ISSN: 2405-6561
DOI: 10.1016/j.petlm.2015.10.011