Abstract
Most recently, attention has turned towards Machine learning techniques to predict software development cost as they are more apt when vague and inaccurate information is to be used. Based on the existing evidences, it is proved that a few of the problems associated with previous models are addressed by soft computing techniques. But, the need for accurate cost prediction in software project management is a challenge till today. In this paper, the analytical structure of a Takagi-Sugeno Fuzzy Logic Controller with two inputs and one output for software development effort estimation with a case study on NASA 93 dataset is discussed. The analytical study is also presented with two sample inputs. The Fuzzy models are developed using triangular and GBell membership functions. The results are compared using various assessment criteria. It has been observed that the fuzzy model with triangular membership function performed better than the other models.
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Rama Sree, S., Ramesh, S. (2016). Analytical Structure of a Fuzzy Logic Controller for Software Development Effort Estimation. In: Behera, H., Mohapatra, D. (eds) Computational Intelligence in Data Mining—Volume 1. Advances in Intelligent Systems and Computing, vol 410. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2734-2_22
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DOI: https://doi.org/10.1007/978-81-322-2734-2_22
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