@conference { ISI:000380387700081, title = {A Learning Adaptation Cases Technique for Fuzzy Analogy-based Software Development Effort Estimation}, booktitle = {2014 SECOND WORLD CONFERENCE ON COMPLEX SYSTEMS (WCCS)}, year = {2014}, note = {2014 Second World Conference on Complex Systems (WCCS), Agadir, MOROCCO, NOV 10-12, 2014}, pages = {492-497}, publisher = {Ibn Zohr Univ; Moroccan Soc of Complex Syst; IEEE Morocco; Int Acad for Syst and Cybernet Sci IASCYS}, organization = {Ibn Zohr Univ; Moroccan Soc of Complex Syst; IEEE Morocco; Int Acad for Syst and Cybernet Sci IASCYS}, abstract = {the aim of this paper is to enhance the Fuzzy Analogy technique for software effort development estimation. Fuzzy Analogy selects the similar projects that will be used in the adaptation step according to the definition of the qualification {\textquoteleft}closely similar{\textquoteright}. The adopted definition consider two projects as closely similar if their similarity is in the vicinity of 1. The qualification {\textquoteleft}closely similar{\textquoteright} is represented by a fuzzy set defined by a fixed threshold which is obtained experimentally from the environment. However, in many cases the available empirical knowledge may not allow estimators to fit the adequate fuzzy representation of the qualification {\textquoteleft}closely similar{\textquoteright}. In this study, we propose an approach to learn this fuzzy representation from the similarities obtained in the retrieval step of the Fuzzy Analogy technique. The proposed method provides for each new project, an adequate threshold by using the quasi-arithmetic mean operators. Indeed, the quasi-arithmetic means operators use weighted similarities to calculate the threshold that often ensures the selection of the closest projects in the adaptation step. This paper also presents an empirical validation of the proposed approach based on the COCOMO{\textquoteright} 81 dataset.}, isbn = {978-1-4799-4647-1}, author = {Ezghari, Soufiane and Zahi, Azeddine and Idri, Ali} } @conference { ISI:000333756100029, title = {Software Cost Estimation by Classical and Fuzzy Analogy for Web Hypermedia Applications: A replicated study}, booktitle = {2013 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING (CIDM)}, year = {2013}, note = {IEEE Symposium on Computational Intelligence and Data Mining (CIDM), Singapore, SINGAPORE, APR 16-19, 2013}, pages = {207-213}, publisher = {IEEE; IEEE Computat Intelligence Soc}, organization = {IEEE; IEEE Computat Intelligence Soc}, abstract = {The aim of this paper is to evaluate and to compare the Classical Analogy and Fuzzy Analogy for software cost estimation on a Web software dataset. Hence, the paper aims to replicate the results of our precedent experiments on this dataset. Moreover, questions regarding the estimates accuracy, the tolerance of imprecision and uncertainty of cost drivers, and the favorable context to use estimation by analogy are discussed. This study approved the usefulness of Fuzzy Analogy for software cost estimation.}, isbn = {978-1-4673-5895-8}, author = {Idri, Ali and Zahi, Azeddine} } @conference { ISI:000259298600002, title = {Software cost estimation models using Radial Basis Function Neural Networks}, booktitle = {SOFTWARE PROCESS AND PRODUCT MEASUREMENT}, series = {Lecture Notes in Computer Science}, volume = {4895}, year = {2008}, note = {Joint Meeting of the International Workshop on Software Measurement (IWSM)/International Conference on Software Process and Product Measurement (MENSURA), Palma de Mallorca, SPAIN, NOV 05-07, 2007}, pages = {21+}, abstract = {Radial Basis Function Neural Networks (RBFN) have been recently studied due to their qualification as an universal function approximation. This paper investigates the use of RBF neural networks for software cost estimation, The focus of this study is on the design of these networks, especially their middle layer composed of receptive fields, using two clustering techniques: the C-means and the APC-III algorithms. A comparison between a RBFN using C-means and a RBFN using APC-III, in terms of estimates accuracy, is hence presented. This study uses the COCOMO{\textquoteright}81 dataset and data on Web applications from the Tukutuku database.}, isbn = {978-3-540-85552-1}, issn = {0302-9743}, author = {Idri, Ali and Zahi, Azeddine and Mendes, Emilia and Zakrani, Abdelali}, editor = {CuadradoGallego, JJ and Braungarten, R and Dumke, RR and Abran, A} }