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Judy C. R. Tseng - One of the best experts on this subject based on the ideXlab platform.

  • A multi-stage fuzzy-grey approach to analyzing Software Development Cost
    Lecture Notes in Computer Science, 2005
    Co-Authors: Tony Cheng-kui Huang, Gwo-jen Hwang, Judy C. R. Tseng
    Abstract:

    Analysis of Software Development Cost is an important issue for both the academic and the commercial circles. There have been many methods proposed to analyze benefits and Costs of Software Development. However, in practical applications, these methods are usually not applicable owing to various unpredictable factors, such as depression, which may affect the budget of Software Development, the changes of computer techniques, which may affect the Cost of Software Development, and the adoption of different management concept, which may affect the enterprise's willingness of investing in Software Development. On the other hand, it is hoped that Software Development Cost could be controlled appropriately while considering multiple requirements. In this paper, we proposed a Multi-Stage Fuzzy-Grey (MSFG) method to cope with these problems. A case study for the Development of an e-training system is also given to demonstrate the benefits of our approach.

  • KES (4) - A multi-stage fuzzy-grey approach to analyzing Software Development Cost
    Lecture Notes in Computer Science, 2005
    Co-Authors: Tony Cheng-kui Huang, Gwo-jen Hwang, Judy C. R. Tseng
    Abstract:

    Analysis of Software Development Cost is an important issue for both the academic and the commercial circles. There have been many methods proposed to analyze benefits and Costs of Software Development. However, in practical applications, these methods are usually not applicable owing to various unpredictable factors, such as depression, which may affect the budget of Software Development, the changes of computer techniques, which may affect the Cost of Software Development, and the adoption of different management concept, which may affect the enterprise's willingness of investing in Software Development. On the other hand, it is hoped that Software Development Cost could be controlled appropriately while considering multiple requirements. In this paper, we proposed a Multi-Stage Fuzzy-Grey (MSFG) method to cope with these problems. A case study for the Development of an e-training system is also given to demonstrate the benefits of our approach.

Sergio Soares - One of the best experts on this subject based on the ideXlab platform.

  • 2012 Special Issue: An evolutionary morphological approach for Software Development Cost estimation
    Neural networks : the official journal of the International Neural Network Society, 2012
    Co-Authors: Ricardo De A Araujo, Adriano L I Oliveira, Sergio Soares, Silvio Romero De Lemos Meira
    Abstract:

    In this work we present an evolutionary morphological approach to solve the Software Development Cost estimation (SDCE) problem. The proposed approach consists of a hybrid artificial neuron based on framework of mathematical morphology (MM) with algebraic foundations in the complete lattice theory (CLT), referred to as dilation-erosion perceptron (DEP). Also, we present an evolutionary learning process, called DEP(MGA), using a modified genetic algorithm (MGA) to design the DEP model, because a drawback arises from the gradient estimation of morphological operators in the classical learning process of the DEP, since they are not differentiable in the usual way. Furthermore, an experimental analysis is conducted with the proposed model using five complex SDCE problems and three well-known performance metrics, demonstrating good performance of the DEP model to solve SDCE problems.

  • Hybrid morphological methodology for Software Development Cost estimation
    Expert Systems with Applications, 2012
    Co-Authors: Ricardo De A Araujo, Sergio Soares, Adriano L I Oliveira
    Abstract:

    In this paper we propose a hybrid methodology to design morphological-rank-linear (MRL) perceptrons in the problem of Software Development Cost estimation (SDCE). In this methodology, we use a modified genetic algorithm (MGA) to optimize the parameters of the MRL perceptron, as well as to select an optimal input feature subset of the used databases, aiming at a higher accuracy level for SDCE problems. Besides, for each individual of MGA, a gradient steepest descent method is used to further improve the MRL perceptron parameters supplied by MGA. Finally, we conduct an experimental analysis with the proposed methodology using six well-known benchmark databases of Software projects, where two relevant performance metrics and a fitness function are used to assess the performance of the proposed methodology, which is compared to classical machine learning models presented in the literature.

  • gradient based morphological approach for Software Development Cost estimation
    International Joint Conference on Neural Network, 2011
    Co-Authors: Ricardo De A Araujo, Adriano L I Oliveira, Sergio Soares, Silvio Romero De Lemos Meira
    Abstract:

    In this paper we present a gradient-based morphological approach to solve the Software Development Cost estimation (SDCE) problem. The proposed approach consists of a dilation-erosion perceptron (DEP) trained by a gradient steepest descent method using the back propagation (BP) algorithm and a systematic approach to overcome the problem of nondifferentiability of morphological operators. Furthermore, we compare the proposed approach with other neural and statistical models using five complex SDCE problems.

  • IJCNN - Gradient-based morphological approach for Software Development Cost estimation
    The 2011 International Joint Conference on Neural Networks, 2011
    Co-Authors: Ricardo De A Araujo, Adriano L I Oliveira, Sergio Soares, Silvio Romero De Lemos Meira
    Abstract:

    In this paper we present a gradient-based morphological approach to solve the Software Development Cost estimation (SDCE) problem. The proposed approach consists of a dilation-erosion perceptron (DEP) trained by a gradient steepest descent method using the back propagation (BP) algorithm and a systematic approach to overcome the problem of nondifferentiability of morphological operators. Furthermore, we compare the proposed approach with other neural and statistical models using five complex SDCE problems.

  • A shift-invariant morphological system for Software Development Cost estimation
    Expert Systems with Applications, 2011
    Co-Authors: Ricardo De A Araujo, Adriano L I Oliveira, Sergio Soares
    Abstract:

    Abstract: This work presents a shift-invariant morphological system to solve the problem of Software Development Cost estimation (SDCE). It consists of a hybrid morphological model, which is a linear combination between a morphological-rank (MR) operator (nonlinear) and a Finite Impulse Response (FIR) operator (linear), referred to as morphological-rank-linear (MRL) filter. A gradient steepest descent method to adjust the MRL filter parameters (learning process), using the Least Mean Squares (LMS) algorithm, and a systematic approach to overcome the problem of non-differentiability of the morphological-rank operator are used to improve the numerical robustness of the training algorithm. Furthermore, an experimental analysis is conducted with the proposed system using the NASA Software project database, and in the experiments, two relevant performance metrics and an evaluation function are used to assess its performance. The results obtained are compared to models recently presented in literature, showing superior performance of this kind of morphological systems for the SDCE problem.

Soaressergio - One of the best experts on this subject based on the ideXlab platform.

Tony Cheng-kui Huang - One of the best experts on this subject based on the ideXlab platform.

  • A multi-stage fuzzy-grey approach to analyzing Software Development Cost
    Lecture Notes in Computer Science, 2005
    Co-Authors: Tony Cheng-kui Huang, Gwo-jen Hwang, Judy C. R. Tseng
    Abstract:

    Analysis of Software Development Cost is an important issue for both the academic and the commercial circles. There have been many methods proposed to analyze benefits and Costs of Software Development. However, in practical applications, these methods are usually not applicable owing to various unpredictable factors, such as depression, which may affect the budget of Software Development, the changes of computer techniques, which may affect the Cost of Software Development, and the adoption of different management concept, which may affect the enterprise's willingness of investing in Software Development. On the other hand, it is hoped that Software Development Cost could be controlled appropriately while considering multiple requirements. In this paper, we proposed a Multi-Stage Fuzzy-Grey (MSFG) method to cope with these problems. A case study for the Development of an e-training system is also given to demonstrate the benefits of our approach.

  • KES (4) - A multi-stage fuzzy-grey approach to analyzing Software Development Cost
    Lecture Notes in Computer Science, 2005
    Co-Authors: Tony Cheng-kui Huang, Gwo-jen Hwang, Judy C. R. Tseng
    Abstract:

    Analysis of Software Development Cost is an important issue for both the academic and the commercial circles. There have been many methods proposed to analyze benefits and Costs of Software Development. However, in practical applications, these methods are usually not applicable owing to various unpredictable factors, such as depression, which may affect the budget of Software Development, the changes of computer techniques, which may affect the Cost of Software Development, and the adoption of different management concept, which may affect the enterprise's willingness of investing in Software Development. On the other hand, it is hoped that Software Development Cost could be controlled appropriately while considering multiple requirements. In this paper, we proposed a Multi-Stage Fuzzy-Grey (MSFG) method to cope with these problems. A case study for the Development of an e-training system is also given to demonstrate the benefits of our approach.

Ricardo De A Araujo - One of the best experts on this subject based on the ideXlab platform.

  • 2012 Special Issue: An evolutionary morphological approach for Software Development Cost estimation
    Neural networks : the official journal of the International Neural Network Society, 2012
    Co-Authors: Ricardo De A Araujo, Adriano L I Oliveira, Sergio Soares, Silvio Romero De Lemos Meira
    Abstract:

    In this work we present an evolutionary morphological approach to solve the Software Development Cost estimation (SDCE) problem. The proposed approach consists of a hybrid artificial neuron based on framework of mathematical morphology (MM) with algebraic foundations in the complete lattice theory (CLT), referred to as dilation-erosion perceptron (DEP). Also, we present an evolutionary learning process, called DEP(MGA), using a modified genetic algorithm (MGA) to design the DEP model, because a drawback arises from the gradient estimation of morphological operators in the classical learning process of the DEP, since they are not differentiable in the usual way. Furthermore, an experimental analysis is conducted with the proposed model using five complex SDCE problems and three well-known performance metrics, demonstrating good performance of the DEP model to solve SDCE problems.

  • Hybrid morphological methodology for Software Development Cost estimation
    Expert Systems with Applications, 2012
    Co-Authors: Ricardo De A Araujo, Sergio Soares, Adriano L I Oliveira
    Abstract:

    In this paper we propose a hybrid methodology to design morphological-rank-linear (MRL) perceptrons in the problem of Software Development Cost estimation (SDCE). In this methodology, we use a modified genetic algorithm (MGA) to optimize the parameters of the MRL perceptron, as well as to select an optimal input feature subset of the used databases, aiming at a higher accuracy level for SDCE problems. Besides, for each individual of MGA, a gradient steepest descent method is used to further improve the MRL perceptron parameters supplied by MGA. Finally, we conduct an experimental analysis with the proposed methodology using six well-known benchmark databases of Software projects, where two relevant performance metrics and a fitness function are used to assess the performance of the proposed methodology, which is compared to classical machine learning models presented in the literature.

  • gradient based morphological approach for Software Development Cost estimation
    International Joint Conference on Neural Network, 2011
    Co-Authors: Ricardo De A Araujo, Adriano L I Oliveira, Sergio Soares, Silvio Romero De Lemos Meira
    Abstract:

    In this paper we present a gradient-based morphological approach to solve the Software Development Cost estimation (SDCE) problem. The proposed approach consists of a dilation-erosion perceptron (DEP) trained by a gradient steepest descent method using the back propagation (BP) algorithm and a systematic approach to overcome the problem of nondifferentiability of morphological operators. Furthermore, we compare the proposed approach with other neural and statistical models using five complex SDCE problems.

  • IJCNN - Gradient-based morphological approach for Software Development Cost estimation
    The 2011 International Joint Conference on Neural Networks, 2011
    Co-Authors: Ricardo De A Araujo, Adriano L I Oliveira, Sergio Soares, Silvio Romero De Lemos Meira
    Abstract:

    In this paper we present a gradient-based morphological approach to solve the Software Development Cost estimation (SDCE) problem. The proposed approach consists of a dilation-erosion perceptron (DEP) trained by a gradient steepest descent method using the back propagation (BP) algorithm and a systematic approach to overcome the problem of nondifferentiability of morphological operators. Furthermore, we compare the proposed approach with other neural and statistical models using five complex SDCE problems.

  • A shift-invariant morphological system for Software Development Cost estimation
    Expert Systems with Applications, 2011
    Co-Authors: Ricardo De A Araujo, Adriano L I Oliveira, Sergio Soares
    Abstract:

    Abstract: This work presents a shift-invariant morphological system to solve the problem of Software Development Cost estimation (SDCE). It consists of a hybrid morphological model, which is a linear combination between a morphological-rank (MR) operator (nonlinear) and a Finite Impulse Response (FIR) operator (linear), referred to as morphological-rank-linear (MRL) filter. A gradient steepest descent method to adjust the MRL filter parameters (learning process), using the Least Mean Squares (LMS) algorithm, and a systematic approach to overcome the problem of non-differentiability of the morphological-rank operator are used to improve the numerical robustness of the training algorithm. Furthermore, an experimental analysis is conducted with the proposed system using the NASA Software project database, and in the experiments, two relevant performance metrics and an evaluation function are used to assess its performance. The results obtained are compared to models recently presented in literature, showing superior performance of this kind of morphological systems for the SDCE problem.