Software effort estimation accuracy prediction of machine learning techniques: A systematic performance evaluation
Software effort estimation accuracy is a key factor in effective planning, controlling, and
delivering a successful software project within budget and schedule. The overestimation and …
delivering a successful software project within budget and schedule. The overestimation and …
Systematic literature review of ensemble effort estimation
The need to overcome the weaknesses of single estimation techniques for prediction tasks
has given rise to ensemble methods in software development effort estimation (SDEE). An …
has given rise to ensemble methods in software development effort estimation (SDEE). An …
An empirical comparison of model validation techniques for defect prediction models
Defect prediction models help software quality assurance teams to allocate their limited
resources to the most defect-prone modules. Model validation techniques, such as-fold …
resources to the most defect-prone modules. Model validation techniques, such as-fold …
Satin bowerbird optimizer: A new optimization algorithm to optimize ANFIS for software development effort estimation
SHS Moosavi, VK Bardsiri - Engineering Applications of Artificial …, 2017 - Elsevier
Accurate software development effort estimation is crucial to efficient planning of software
projects. Due to complex nature of software projects, development effort estimation has …
projects. Due to complex nature of software projects, development effort estimation has …
[HTML][HTML] Analysis and selection of a regression model for the use case points method using a stepwise approach
This study investigates the significance of use case points (UCP) variables and the influence
of the complexity of multiple linear regression models on software size estimation and …
of the complexity of multiple linear regression models on software size estimation and …
Design ensemble deep learning model for pneumonia disease classification
K El Asnaoui - International Journal of Multimedia Information …, 2021 - Springer
With the recent spread of the SARS-CoV-2 virus, computer-aided diagnosis (CAD) has
received more attention. The most important CAD application is to detect and classify …
received more attention. The most important CAD application is to detect and classify …
Ensemble learning with member optimization for fault diagnosis of a building energy system
H Han, Z Zhang, X Cui, Q Meng - Energy and Buildings, 2020 - Elsevier
For better service and energy savings, improved fault detection and diagnosis (FDD) of
building energy systems is of great importance. To achieve this aim, ensemble learning is …
building energy systems is of great importance. To achieve this aim, ensemble learning is …
Research patterns and trends in software effort estimation
Context Software effort estimation (SEE) is most crucial activity in the field of software
engineering. Vast research has been conducted in SEE resulting into a tremendous …
engineering. Vast research has been conducted in SEE resulting into a tremendous …
Deep hybrid architectures for diabetic retinopathy classification
Diabetic retinopathy (DR) is the most severe ocular complication of diabetes. It leads to
serious eye complications such as vision impairment and blindness. A computer-aided …
serious eye complications such as vision impairment and blindness. A computer-aided …
On the value of deep learning for diagnosing diabetic retinopathy
Diabetic retinopathy (DR) is one of the main causes of vision loss around the world. The
early diagnosis of this disease can help in treating it efficiently. Deep learning (DL) is rapidly …
early diagnosis of this disease can help in treating it efficiently. Deep learning (DL) is rapidly …