A fuzzy neural network for web service selection aimed at dynamic software rejuvenation

2020 ◽  
Vol 28 (5) ◽  
pp. 2718-2734
Author(s):  
Kimia REZAEI KALANTARI ◽  
Ali EBRAHIMNEJAD ◽  
Homayun MOTAMENI
Keyword(s):  
Neural Network ◽  
Web Service ◽  
Fuzzy Neural Network ◽  
Service Selection ◽  
Software Rejuvenation ◽  
Web Service Selection ◽  
Fuzzy Neural ◽  
Dynamic Software

A fuzzy neural network approach for modeling the growth kinetics of FeB and Fe2B layers during the boronizing process

2018 ◽  
Vol 106 (6) ◽  
pp. 603 ◽  
Author(s):  
Bendaoud Mebarek ◽  
Mourad Keddam
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Fuzzy Neural Network ◽  
Treatment Time ◽  
Calculation Model ◽  
Average Error ◽  
Network Approach ◽  
Neural Network Approach ◽  
Fuzzy Neural ◽  
Kinetics Of

In this paper, we develop a boronizing process simulation model based on fuzzy neural network (FNN) approach for estimating the thickness of the FeB and Fe2B layers. The model represents a synthesis of two artificial intelligence techniques; the fuzzy logic and the neural network. Characteristics of the fuzzy neural network approach for the modelling of boronizing process are presented in this study. In order to validate the results of our calculation model, we have used the learning base of experimental data of the powder-pack boronizing of Fe-15Cr alloy in the temperature range from 800 to 1050 °C and for a treatment time ranging from 0.5 to 12 h. The obtained results show that it is possible to estimate the influence of different process parameters. Comparing the results obtained by the artificial neural network to experimental data, the average error generated from the fuzzy neural network was 3% for the FeB layer and 3.5% for the Fe2B layer. The results obtained from the fuzzy neural network approach are in agreement with the experimental data. Finally, the utilization of fuzzy neural network approach is well adapted for the boronizing kinetics of Fe-15Cr alloy.

Inverse Control of Cable-driven Parallel Mechanism Using Type-2 Fuzzy Neural Network

2010 ◽  
Vol 36 (3) ◽  
pp. 459-464 ◽  
Author(s):  
Cheng-Dong LI ◽  
Jian-Qiang YI ◽  
Yi YU ◽  
Dong-Bin ZHAO
Keyword(s):  
Neural Network ◽  
Parallel Mechanism ◽  
Fuzzy Neural Network ◽  
Inverse Control ◽  
Fuzzy Neural

Method of Top-k Web service selection based on QoS

2010 ◽  
Vol 30 (4) ◽  
pp. 872-875
Author(s):  
Hai WANG ◽  
Zheng-dong ZHU ◽  
Zeng-zhi LI
Keyword(s):  
Web Service ◽  
Service Selection ◽  
Web Service Selection
Sign in / Sign up

Export Citation Format

Share Document