Software Effort Estimation using Neuro Fuzzy Inference System: Past and Present
December 26, 2019 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Aditi Sharma, Ravi Ranjan
arXiv ID
1912.11855
Category
cs.SE: Software Engineering
Cross-listed
cs.LG
Citations
7
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Most important reason for project failure is poor effort estimation. Software development effort estimation is needed for assigning appropriate team members for development, allocating resources for software development, binding etc. Inaccurate software estimation may lead to delay in project, over-budget or cancellation of the project. But the effort estimation models are not very efficient. In this paper, we are analyzing the new approach for estimation i.e. Neuro Fuzzy Inference System (NFIS). It is a mixture model that consolidates the components of artificial neural network with fuzzy logic for giving a better estimation.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted