Point Kernel Modification Including Support Vector Regression Neutron Buildup Factor Models
نویسندگان
چکیده
This work presents the results of radiation shielding calculations using modified point kernel code QAD-CGGP. The modification includes a new approach to neutron buildup factor estimations based on machine learning technique called Support vector regression (SVR). SVR models for common materials are developed and built into development consisted acquiring data be used model, optimizing parameters, application active methods improving process. is tested, compared with MCNP6 results.
منابع مشابه
Kernel Support Vector Regression with imprecise output ∗
We consider a regression problem where uncertainty affects to the dependent variable of the elements of the database. A model based on the standard -Support Vector Regression approach is given, where two hyperplanes need to be constructed to predict the interval-valued dependent variable. By using the Hausdorff distance to measure the error between predicted and real intervals, a convex quadrat...
متن کاملMultiple Kernel Learning for Support Vector Regression ∗
Kernel support vector (SV) regression has successfully been used for prediction of nonlinear and complicated data. However, like other kernel methods such as support vector machine (SVM) classification, the quality of SV regression depends on proper choice of kernel functions and their parameters. Kernel selection for model selection is conventionally performed through repeated cross validation...
متن کاملUse Case Point Approach Based Software Effort Estimation using Various Support Vector Regression Kernel Methods
The job of software effort estimation is a critical one in the early stages of the software development life cycle when the details of requirements are usually not clearly identified. Various optimization techniques help in improving the accuracy of effort estimation. The Support Vector Regression (SVR) is one of several different soft-computing techniques that help in getting optimal estimated...
متن کاملSupport Vector Machines, Kernel Logistic Regression and Boosting
The support vector machine is known for its excellent performance in binary classification, i.e., the response y ∈ {−1, 1}, but its appropriate extension to the multi-class case is still an on-going research issue. Another weakness of the SVM is that it only estimates sign[p(x) − 1/2], while the probability p(x) is often of interest itself, where p(x) = P (Y = 1|X = x) is the conditional probab...
متن کاملMultiple kernel support vector regression for pricing nifty option
The goal of present experiments is to investigate the use of multiple kernel learning as a tool for pricing options in the context of Indian stock market for Nifty index options. In this paper, fair price of an option is predicted by Multiple Kernel Support Vector Regression (MKLSVR) using linear combinations of kernels and Single Kernel Support Vector Regression (SKSVR). Prices of option highl...
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: Energija
سال: 2022
ISSN: ['0354-8651', '2812-7528']
DOI: https://doi.org/10.37798/2019682-3200