Journal ArticleDOI
Fuzzy systems and neural networks in software engineering project management
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TLDR
It is shown that the MBI selection process can be based upon 64 different fuzzy associative memory (FAM) rules, and the same rules are used to generate 64 training patterns for a feedforward neural network.Abstract:
To make reasonable estimates of resources, costs, and schedules, software project managers need to be provided with models that furnish the essential framework for software project planning and control by supplying important “management numbers” concerning the state and parameters of the project that are critical for resource allocation. Understanding that software development is not a “mechanistic” process brings about the realization that parameters that characterize the development of software possess an inherent “fuzziness,” thus providing the rationale for the development of realistic models based on fuzzy set or neural theories.read more
Citations
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Journal ArticleDOI
An investigation of artificial neural networks based prediction systems in software project management
TL;DR: Artificial neural network and stepwise regression based predictive models are investigated, aiming at offering alternative methods for those who do not believe in estimation models and indicate that these techniques are competitive with the APF, SLIM, and COCOMO methods.
Journal ArticleDOI
Adaptive fuzzy logic-based framework for software development effort prediction
TL;DR: An adaptive fuzzy logic framework for software effort prediction that tolerates imprecision, explains prediction rationale through rules, incorporates experts knowledge, offers transparency in the prediction system, and could adapt to new environments as new data becomes available is presented.
Proceedings ArticleDOI
A comparison of development effort estimation techniques for Web hypermedia applications
TL;DR: This paper compares the prediction accuracy of three CBR techniques to estimate the effort to develop Web hypermedia applications against three commonly used prediction models, namely multiple linear regression, stepwise regression and regression trees.
Proceedings ArticleDOI
Applications of fuzzy logic to software metric models for development effort estimation
TL;DR: Software metrics are measurements of the software development process and product that can be used as variables (both dependent and independent) in models for project management and the use of alternative techniques, especially fuzzy logic, is investigated and some usage recommendations are made.
Journal ArticleDOI
Bayesian Regularization in a Neural Network Model to Estimate Lines of Code Using Function Points
TL;DR: Results demonstrate that the neural network models trained using Bayesian Regularization provide the best results and are suitable for estimating the Source Lines of Code.
References
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Book ChapterDOI
Learning internal representations by error propagation
TL;DR: This chapter contains sections titled: The Problem, The Generalized Delta Rule, Simulation Results, Some Further Generalizations, Conclusion.
Journal ArticleDOI
Neural networks and physical systems with emergent collective computational abilities
TL;DR: A model of a system having a large number of simple equivalent components, based on aspects of neurobiology but readily adapted to integrated circuits, produces a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size.
MonographDOI
Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations
Book
Learning internal representations by error propagation
TL;DR: In this paper, the problem of the generalized delta rule is discussed and the Generalized Delta Rule is applied to the simulation results of simulation results in terms of the generalized delta rule.
Book
Self Organization And Associative Memory
TL;DR: The purpose and nature of Biological Memory, as well as some of the aspects of Memory Aspects, are explained.