Gecynalda Soares da Silva Gomes

According to our database1, Gecynalda Soares da Silva Gomes authored at least 12 papers between 2006 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Machine learning models for forecasting water demand for the Metropolitan Region of Salvador, Bahia.
Neural Comput. Appl., September, 2023

2022
Forecasting daily Covid-19 cases in the world with a hybrid ARIMA and neural network model.
Appl. Soft Comput., 2022

2019
Investigating Variability-aware Smells in SPLs: An Exploratory Study.
Proceedings of the XXXIII Brazilian Symposium on Software Engineering, 2019

2018
On the implementation of dynamic software product lines: An exploratory study.
J. Syst. Softw., 2018

2017
Evaluating Lehman's Laws of software evolution within software product lines industrial projects.
J. Syst. Softw., 2017

2016
Evaluating Variability Modeling Techniques for Dynamic Software Product Lines: A Controlled Experiment.
Proceedings of the 2016 X Brazilian Symposium on Software Components, 2016

On the Implementation of Dynamic Software Product Lines: A Preliminary Study.
Proceedings of the 2016 X Brazilian Symposium on Software Components, 2016

2015
Evaluating Lehman's Laws of Software Evolution within Software Product Lines: A Preliminary Empirical Study.
Proceedings of the Software Reuse for Dynamic Systems in the Cloud and Beyond, 2015

2013
Evidence of software inspection on feature specification for software product lines.
J. Syst. Softw., 2013

2012
On the Relationship between Inspection and Evolution in Software Product Lines: An Exploratory Study.
Proceedings of the 26th Brazilian Symposium on Software Engineering, 2012

2006
Hybrid model with dynamic architecture for forecasting time series.
Proceedings of the International Joint Conference on Neural Networks, 2006

Feature Selection for Neural Networks Through Binomial Regression.
Proceedings of the Neural Information Processing, 13th International Conference, 2006


  Loading...