Optimization of the automotive air conditioning system using radial basis function neural network
نویسندگان
چکیده
The defrosting performance of automotive air conditioners plays an important role in driving safety. This paper uses CFD to simulate the internal flow field automobile numerically. Simulation results show that distribution is unreasonable. horizontal grilles are added at outlets improve automobile. Air-flow jet angle and length conditioning (L1, L2) selected as design variables based on radial basis neural network find optimal combination scheme. area dead corner has been reduced from 20-5% after optimization, frost layer front windshield completely melted 25 minutes. experiment test conducted verify improvement conditioners. methodology can be applied development conditioner.
منابع مشابه
Fast 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 کاملRadial-Basis-Function Neural Network Optimization of Microwave Systems
An original approach in microwave optimization, namely, a neural network procedure combined with the full-wave 3D electromagnetic simulator QuickWave-3D implemented a conformal FDTD method, is presented. The radial-basis-function network is trained by simulated frequency characteristics of S-parameters and geometric data of the corresponding system. High accuracy and computational efficiency 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 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 کاملIdentification of Nonlinear Systems Using Radial Basis Function Neural Network
Abstract—This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for mod...
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: Thermal Science
سال: 2022
ISSN: ['0354-9836', '2334-7163']
DOI: https://doi.org/10.2298/tsci210225280f