Volume 7 Issue 2 - July 2016

  • 1. Reliability assessment by using neural network and fuzzy analysis for the software cost effective evolution exertion

    Authors : Lakshmana Rao Padala, Dr. E Mohan

    Pages : 388-393

    DOI : http://dx.doi.org/10.21172/1.72.561

    Keywords : Fuzzy Logic, bi-logic, multi-logic, Project Management, Requirement Specifications, MUSE

    Abstract :

    Fuzzy logic is a mathematical model used for different applications indexing from the control of engineering system to artificial intelligence. Application of fuzzy logic improves a better set of solution. The Software schema, applies the fuzzy logic to increase the quality of product involving the human knowledge and experience. The main theme of the paper is to describe the software engineering principles applied to improve the process of working with fuzzy logic. The system software development process is devised by a standard project failure. Basic reason for the project failure is due to lack of requirement specification engineering, which has to be broadly classified and iteratively discussed and documented. Other factors like impecunious project management exercise, impecunious design tactic and incapable of testing methods also contributing to project failures. The main reason of fit fall is that we use traditional bi-logic structure for decision making. The output of the process is either yes or no in bi-logic system. The Maxim of Uncertainty in Software Engineering (MUSE) states that the unpredictable in genetic and irresistible in software development processes and products. The above fit falls can be easily solved by the Fuzzy logic, because fuzzy logic has ability to deal with unpredictable and multi-logic e.g. an individual problem domain has 0.5 probability or 0.8 probability to be taken as a class, whereas in classical bi-logic, there is only two probability values either 0 or 1. So, measurement levels increases from bi-logic to multi-logic, consequently the measurement error will be reduced and minor data loss at initial stage of evolution. Fuzzy logic uses membership functions to absorb multi variants and values.

    Citing this Journal Article :

    Lakshmana Rao Padala, Dr. E Mohan , "Reliability assessment by using neural network and fuzzy analysis for the software cost effective evolution exertion", https://www.ijltet.org/journal_details.php?id=906&j_id=3265, Volume 7 Issue 2 - July 2016, 388-393, #ijltetorg