@Article{jcs.2020.014045,
AUTHOR = {Yu Xue, Sow Alpha Amadou, Yan Zhao},
TITLE = {Improvement of the Firework Algorithm for Classification Problems},
JOURNAL = {Journal of Cyber Security},
VOLUME = {2},
YEAR = {2020},
NUMBER = {4},
PAGES = {191--196},
URL = {http://www.techscience.com/JCS/v2n4/40716},
ISSN = {2579-0064},
ABSTRACT = {Attracted numerous analysts’ consideration, classification is one of the 
primary issues in Machine learning. Numerous evolutionary algorithms (EAs) 
were utilized to improve their global search ability. In the previous years, many 
scientists have attempted to tackle this issue, yet regardless of the endeavors, 
there are still a few inadequacies. Based on solving the classification problem, 
this paper introduces a new optimization classification model, which can be 
applied to the majority of evolutionary computing (EC) techniques. Firework 
algorithm (FWA) is one of the EC methods, Although the Firework algorithm 
(FWA) is a proficient algorithm for solving complex optimization issue. The 
proficient of the FWA isn't fulfilled when being utilized for solving the 
classification issues. In this paper we previously proposed optimization 
classification model according to the classification issue. At that point we 
legitimately utilize the model with FWA to solve the classification issue. Finally, 
to investigate the performance of our model, we select 4 datasets in the 
experiments, and the results indicate that an improved FWA can upgrade the 
classification accuracy by using this model.},
DOI = {10.32604/jcs.2020.014045}
}