A Novel Framework for Evaluating the Software Project Management Efficiency-An Artificial Intelligence Approach
The main purpose of this work is to find a suitable solution for improving the efficiency of the Software Project Management (SPM). In this work we have used a novel artificial intelligence method, a fuzzy logic approach to evaluate the SPM efficiency. There are many IT organization suffers on manag...
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2014-09-01.
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| Online Access: | Get fulltext |
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| LEADER | 02456 am a22002773u 4500 | ||
|---|---|---|---|
| 001 | ijeecs3848_2312 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Govindarajan, Anandhi |e author |
| 245 | 0 | 0 | |a A Novel Framework for Evaluating the Software Project Management Efficiency-An Artificial Intelligence Approach |
| 260 | |b Institute of Advanced Engineering and Science, |c 2014-09-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3848 | ||
| 520 | |a The main purpose of this work is to find a suitable solution for improving the efficiency of the Software Project Management (SPM). In this work we have used a novel artificial intelligence method, a fuzzy logic approach to evaluate the SPM efficiency. There are many IT organization suffers on managing the SPM, it may be due to several reasons such as project work can't begin on time, it may have vague requirements, people involved in the project can't stay within project parameters, unity among the people involved in the projects and improper communication unclear project objectives and goals. All these issues usually may lead to delay in the project and have greater impact on the project failure, which in turn causes the poor Software Project Management efficiency.Fuzzy logic is one of the Artificial Intelligence method helps to solve the problems when there is a SPM with uncertainty and vagueness in it. We used the fuzzy inference system (FIS) to quantify the SPM efficiency under uncertainty and vagueness of the parameters involved in quantifying SPM efficiency. The outcome of the work is really appreciable and encouraging to quantify the Software Project Management efficiency | ||
| 540 | |a Copyright (c) 2014 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc-nd/4.0 | ||
| 546 | |a eng | ||
| 690 | |a Electrical and Electronics | ||
| 690 | |a Software Project Management, Fuzzy Inference System, Artificial Intelligence. | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 12, No 9: September 2014; 7054-7058 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v12.i9 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3848/2312 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3848/2312 |z Get fulltext |