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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Proceedings ArticleDOI
Do adaptation rules improve web cost estimation
TL;DR: This paper compares several methods of analogy-based effort estimation and investigates the use of adaptation rules as a contributing factor to better estimation accuracy, finding only one of the two types of adaptation Rules employed generated good predictions.
Proceedings ArticleDOI
Reliability Growth Modeling for Software Fault Detection Using Particle Swarm Optimization
TL;DR: The proposed approach will be used to estimate the parameters of the well known reliability growth models such as the exponential model, power model and S-shaped models and the results are promising.
Using Machine Learning to Predict Project Effort: Empirical Case Studies in Data-Starved Domains
TL;DR: This paper conducts a set of machine learning experiments with software cost estimation data from two separate organizations to explore the possibility of performing project estimating from a bottom-up perspective and characterize predictive potential within two different organizations.
Reliability Growth Modeling for Software Fault Detection Using Particle Swarm
TL;DR: In this article, a pre- liminary idea in using Particle Swarm Optimization (PSO) technique to help in solving the reliability growth modeling problem is explored, and the proposed approach will be used to estimate the parameters of the well known reliability growth models such as the exponential model, power model and S-Shaped models.
Alternatives to regression models for estimating software projects
TL;DR: The use of ‘standard’ regression analysis to derive predictive equations for software development has recently been complemented by increasing numbers of analyses using less common methods, such as neural networks, fuzzy logic models, and regression trees.
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.