Nailah Al-Madi

According to our database1, Nailah Al-Madi authored at least 13 papers between 2012 and 2020.

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

Timeline

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PhD thesis 
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Links

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Bibliography

2020
Cost-sensitive ensemble methods for bankruptcy prediction in a highly imbalanced data distribution: a real case from the Spanish market.
Prog. Artif. Intell., 2020

A dynamic locality multi-objective salp swarm algorithm for feature selection.
Comput. Ind. Eng., 2020

2019
Binary multi-verse optimization algorithm for global optimization and discrete problems.
Int. J. Mach. Learn. Cybern., 2019

Evolving neural networks using bird swarm algorithm for data classification and regression applications.
Clust. Comput., 2019

2018
Training radial basis function networks using biogeography-based optimizer.
Neural Comput. Appl., 2018

The Influence of Input Data Standardization Methods on the Prediction Accuracy of Genetic Programming Generated Classifiers.
Proceedings of the 10th International Joint Conference on Computational Intelligence, 2018

2016
Optimizing the Learning Process of Feedforward Neural Networks Using Lightning Search Algorithm.
Int. J. Artif. Intell. Tools, 2016

Mike Preuss: Multimodal optimization by means of evolutionary algorithms - Springer, 2015, 175 pp, ISBN: 978-3-319-07407-8.
Genet. Program. Evolvable Mach., 2016

2014
Parallel glowworm swarm optimization clustering algorithm based on MapReduce.
Proceedings of the 2014 IEEE Symposium on Swarm Intelligence, 2014

2013
Scaling Genetic Programming for data classification using MapReduce methodology.
Proceedings of the Fifth World Congress on Nature and Biologically Inspired Computing, 2013

Segment-based genetic programming.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Improving genetic programming classification for binary and multiclass datasets.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2013

2012
Adaptive genetic programming applied to classification in data mining.
Proceedings of the Fourth World Congress on Nature and Biologically Inspired Computing, 2012


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