An Application of Neural Network in Method for Use Case Based Effort Estimation

被引：0
|
作者：
Strba, Radoslav [1 ]
Stolfa, Svatopluk [1 ]
Stolfa, Jakub [1 ]
Vondrak, Ivo [1 ]
Snasel, Vaclav [1 ]
机构：
[1] VSB Tech Univ Ostrava, Dept Comp Sci, Fac Elect Engn & Comp Sci, Ostrava 70833, Czech Republic
来源：
INFORMATION MODELLING AND KNOWLEDGE BASES XXVIII | 2017年 / 292卷
关键词：
Effort Estimation; Use Case; Artificial Neural Network; Backpropagation Softmax Function; Hyperbolic Tangent Function; SOFTWARE COST ESTIMATION; CLASSIFICATION; MODELS;
D O I：
10.3233/978-1-61499-720-7-231
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Effort overruns is common problem in software development. Our main intention is to support estimation by method for classification of use cases. The goal of this paper is to evaluate usage of the feed-forward neural network for the Use Case classification purposes. Experimental results show that the feed-forward neural network classifier, using softmax activation function in the output layer and hyperbolic tangent activation function in the hidden layer, offers the best classification performance.
引用
收藏
页码：231 / 248
页数：18
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