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A Hybrid Approach for Requirements Prioritization Using LFPP and ANN
Author(s) -
Yash Veer Singh,
Bijendra Kumar,
Satish Chand
Publication year - 2019
Publication title -
international journal of intelligent systems and applications
Language(s) - English
Resource type - Journals
eISSN - 2074-9058
pISSN - 2074-904X
DOI - 10.5815/ijisa.2019.01.02
Subject(s) - requirement prioritization , computer science , multiple criteria decision analysis , prioritization , analytic hierarchy process , rank (graph theory) , software requirements , software , fuzzy logic , process (computing) , requirements engineering , reliability engineering , operations research , risk analysis (engineering) , requirements management , artificial intelligence , software development , management science , software design , mathematics , economics , medicine , combinatorics , engineering , programming language , operating system
Requirements prioritization is a most important activity to rank the requirements as per their priority of order .It is a crucial phase of requirement engineering in software development process. In this research introduced a MCDM model for requirements prioritization. To select a best supplier firm of washing machine three important criteria are used. In this proposed model investigation for requirements prioritization, a case study adopted from Ozcan et al using LOG FAHP (Logarithmic fuzzy analytic hierarchy process) and ANN (Artificial Neural Network) based model to choose the best supplier firm granting the highest client satisfaction among all technical aspects. The test was conducted on MATLAB software and result evaluated on fuzzy comparison matrix with three supplier selection criteria based on FAHP and LOGANFIS that shows the decision making outcome for requirements prioritization is better than existing approaches with higher priority.

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