A comprehensive survey on recent metaheuristics for feature selection
Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …
preprocessing due to the ever-increasing sizes in actual data. There have been many …
Metaheuristic algorithms on feature selection: A survey of one decade of research (2009-2019)
Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …
dimension of the feature set while maintaining the accuracy of the performance is the main …
A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions
With the increase in the usage of the Internet, a large amount of information is exchanged
between different communicating devices. The data should be communicated securely …
between different communicating devices. The data should be communicated securely …
A review of the modification strategies of the nature inspired algorithms for feature selection problem
This survey is an effort to provide a research repository and a useful reference for
researchers to guide them when planning to develop new Nature-inspired Algorithms …
researchers to guide them when planning to develop new Nature-inspired Algorithms …
The monarch butterfly optimization algorithm for solving feature selection problems
Feature selection (FS) is considered to be a hard optimization problem in data mining and
some artificial intelligence fields. It is a process where rather than studying all of the features …
some artificial intelligence fields. It is a process where rather than studying all of the features …
S-shaped binary whale optimization algorithm for feature selection
Whale optimization algorithm is one of the recent nature-inspired optimization technique
based on the behavior of bubble-net hunting strategy. In this paper, a novel binary version of …
based on the behavior of bubble-net hunting strategy. In this paper, a novel binary version of …
Binary whale optimization algorithm for dimensionality reduction
Feature selection (FS) was regarded as a global combinatorial optimization problem. FS is
used to simplify and enhance the quality of high-dimensional datasets by selecting …
used to simplify and enhance the quality of high-dimensional datasets by selecting …
New brain tumor classification method based on an improved version of whale optimization algorithm
B Yin, C Wang, F Abza - Biomedical Signal Processing and Control, 2020 - Elsevier
Brain tumor is an abnormal growth of cells in the brain that its diagnosis in the early stages
can help us to prevent the dangers of the next stage. In this paper, a new meta-heuristic …
can help us to prevent the dangers of the next stage. In this paper, a new meta-heuristic …
Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm
Forecasting streamflow is vital for strategically planning, utilizing and redistributing water
resources. In this paper, a wavelet-hybrid artificial neural network (ANN) model integrated …
resources. In this paper, a wavelet-hybrid artificial neural network (ANN) model integrated …
Application of firefly algorithm-based support vector machines for prediction of field capacity and permanent wilting point
Soil field capacity (FC) and permanent wilting point (PWP) are significant parameters in
numerous biophysical models and agricultural activities. Although these parameters can be …
numerous biophysical models and agricultural activities. Although these parameters can be …