Comparison of ANFIS with MLP ANN in Measuring the Reliability based on Aspect Oriented Software

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Mohammad Zavvar 1,* Farhad Ramezani 1

1. Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran

* Corresponding author.


Received: 10 Jun. 2015 / Revised: 7 Jul. 2015 / Accepted: 6 Aug. 2015 / Published: 8 Sep. 2015

Index Terms

Adaptive Fuzzy Neural Network, Artificial Neural Network, Reliability, Aspect Oriented Software


In fact, Reliability as the qualities metric is the probability success or The probability that a system or set of tasks without failure for a specified constraints of time and space, as specified in the design and operating conditions specified temperature, humidity, vibration and action. A relatively new methodologies for developing complex software systems engineering is an aspect-oriented software systems, that provides the new methods for the separation of concerns multiple module configuration or intervention and automatic integration them with a system. In this paper, using MLP artificial neural networks and adaptive fuzzy neural network assess the reliability of the aspect oriented software and at the end, two methods were compared with each other. After examination, the root means square error method based on artificial neural networks, fuzzy neural network-based method of 0.024262 and 0.021874 to be adaptive. The results show that the method is based on adaptive fuzzy neural networks with low error in the estimation of reliability, performance is better than the MLP artificial neural network approach.

Cite This Paper

Mohammad Zavvar, Farhad Ramezani, "Comparison of ANFIS with MLP ANN in Measuring the Reliability based on Aspect Oriented Software", International Journal of Modern Education and Computer Science (IJMECS), vol.7, no.9, pp.29-35, 2015. DOI:10.5815/ijmecs.2015.09.04


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