A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Filters
A New Hybrid Ant Colony Optimization Based on Brain Storm Optimization for Feature Selection
2019
IEICE transactions on information and systems
Data preprocessing especially feature selection is helpful for improving the performance of those algorithms. A new powerful feature selection algorithm is proposed. ...
It combines the advantages of ant colony optimization and brain storm optimization which simulates the behavior of human beings. ...
As mentioned above, BSO simulates the process of brain storm of human beings, but it is not fit for the problem of feature selection because it only generates individual composed of continuous values. ...
doi:10.1587/transinf.2019edl8001
fatcat:f7q3jexx4jecrkys7regyrw5cu
Preface
2021
Natural Computing
bacteria-inspired based feature selection method. ...
The experimental results for nine imbalance datasets show that variable-length brain storm optimization algorithm can find better parameters of CCR-ELM, resulting in the better classification accuracy ...
doi:10.1007/s11047-021-09850-6
fatcat:77rje65z3rdvvjd4pvxecf2wfe
A Clustering-Guided Integer Brain Storm Optimizer for Feature Selection in High-Dimensional Data
2021
Discrete Dynamics in Nature and Society
For high-dimensional data with a large number of redundant features, existing feature selection algorithms still have the problem of "curse of dimensionality." ...
In view of this, the paper studies a new two-phase evolutionary feature selection algorithm, called clustering-guided integer brain storm optimization algorithm (IBSO-C). ...
Brain Storm Optimization Algorithm. In BSO, an idea (i.e., an individual) represents a potential solution of optimized problem. ...
doi:10.1155/2021/8462493
fatcat:jrdgd2sfbbhhtfkmqialvosqvi
Classification Based on Brain Storm Optimization with Feature Selection
2020
IEEE Access
INDEX TERMS Brain storm optimization (BSO) algorithm, classification, evolutionary computation (EC), feature selection. 16582 This work is licensed under a Creative Commons Attribution 4.0 License. ...
Then, the BSO algorithm is employed to implement the evolutionary classification model to search the optimal structure by search for the optimal feature subset. ...
BRAIN STORM OPTIMIZATION ALGORITHM In recent years, many EAs have emerged and the BSO algorithm is one of the popular algorithms, which proposed by Professor Shi [27] in 2011. ...
doi:10.1109/access.2020.3045970
fatcat:cdmnhvslnjg35nqbaanbitq6ea
A Hybrid multi-stage Learning technique based on Brain Storming Optimization algorithm for Breast Cancer Recurrence Prediction
2021
Journal of King Saud University: Computer and Information Sciences
., A Hybrid multi-stage Learning technique based on Brain Storming Optimization algorithm for Breast Cancer Recurrence Abstract: Breast cancer disease is considered to be the second leading reason for ...
The proposed multi-stages technique consists of three main stages; first, the statistical feature selection methods (SFM) which statistically select the discriminative features based on importance ranking ...
Brain Storming Optimization (BSO) is an optimization algorithm proposed by Shi in 2011 [32] . ...
doi:10.1016/j.jksuci.2021.05.004
fatcat:2ifbn4ohm5gmpe7ounckrascve
New Solution Generation Strategy to Improve Brain Storm Optimization Algorithm for Classification
2021
Journal on Internet of Things
As a new intelligent optimization method, brain storm optimization (BSO) algorithm has been widely concerned for its advantages in solving classical optimization problems. ...
Therefore, we briefly introduce the optimization model structure by feature selection. ...
based on BSO (CBSO). ≤ + + + ≤ + − ≤ + + + ≤ + − ≤ + + + ≤ +
Evolutionary Classification Optimization Model with Feature Selection Feature selection is an effective way of data ...
doi:10.32604/jiot.2021.014980
fatcat:vp2aql7tezaxjpvish36oo6pfy
A decision support system for multimodal brain tumor classification using deep learning
2021
Complex & Intelligent Systems
However, the characteristics of this layer are not sufficient for a precise classification; therefore, two techniques for the selection of features are proposed. ...
In this article, a new automated deep learning method is proposed for the classification of multiclass brain tumors. ...
[37] presented segmentation and classification techniques with the help of a fuzzy brain-storm optimization algorithm. ...
doi:10.1007/s40747-021-00321-0
fatcat:c6dwvh5n2rgo3ptwseyerwhtgu
Survey on data science with population-based algorithms
2016
Big Data Analytics
Based on the combination of population-based algorithms and data mining techniques, we understand better the insights of data analytics, and design more efficient algorithms to solve real-world big data ...
Also, the weakness and strength of population-based algorithms could be analyzed via the data analytics along the optimization process, a crucial entity in population-based algorithms. ...
Brain storm optimization The brain storm optimization (BSO) algorithm was proposed in 2011 [4, 5] , which is a young and promising algorithm in swarm intelligence. ...
doi:10.1186/s41044-016-0003-3
fatcat:jvddmsjmivdejehqdwlkm2csca
Intrusion Detection in IoT based Smart Networks using Fuzzy Brain Storm Optimization Technique
2019
International Journal of Engineering and Advanced Technology
This paper proposed a fuzzy c-means clustering with brain storm optimization algorithm (FBSO) for IDS based on IoT system. ...
Therefore there is an essential requirement for IDS for the IoT based systems for avoiding security attacks based on security vulnerabilities. ...
Intrusion Detection in IoT based Smart Networks using Fuzzy Brain Storm Optimization Technique Suresh B, Venkatachalam M, Saroja M
Table .1. ...
doi:10.35940/ijeat.f8651.088619
fatcat:cgj7rvck6vdhfgfgikmzof4fpy
Artificial Intelligence and Data Mining 2014
2014
Abstract and Applied Analysis
Sun, a novel hybrid model based on the brain storm optimization approach is constructed for stock index forecast. ...
In "A hybrid approach by integrating brain storm optimization algorithm with grey neural network for stock index forecasting," authored by Y. ...
Acknowledgments The guest editors of this special issue would like to express their thanks to the authors who have submitted papers for consideration and the referees of the submitted papers. ...
doi:10.1155/2014/819641
fatcat:ktzo3xoqn5f4zkg6jienbohscq
A Deep Learning Model for Detecting Dust in Earth's Atmosphere from Satellite Remote Sensing Data
2020
2020 IEEE International Conference on Smart Computing (SMARTCOMP)
The radiometric channels and geometric parameters from VIIRS (Visible Infrared Imaging Radiometer Suite) satellite sensor serve as features for our model. ...
The occurrence of dust storms is increasing along with global climate change, especially in the arid and semi-arid regions. ...
We also developed a method based on genetic algorithm to find the best subset of features for dust detection. ...
doi:10.1109/smartcomp50058.2020.00045
dblp:conf/smartcomp/HouGWWGZ20
fatcat:52rhmbfmqjdk7nlan27aaaiziq
Editorial
2019
Memetic Computing
In previous issue, we ran a thematic on brain storm optimization (BSO), a novel evolutionary algorithm inspired by the way humans carry out brainstorming process. ...
The other paper on ELM is by Lu et al. with the proposal of an improved weighted ELM for imbalanced data classification. They incorporated a voting scheme to eliminate classes that are not useful. ...
In previous issue, we ran a thematic on brain storm optimization (BSO), a novel evolutionary algorithm inspired by the way humans carry out brainstorming process. ...
doi:10.1007/s12293-019-00281-6
fatcat:kplcxrfb6bfo5icdubwb5hbaoy
Brain Tumor Classification for MR Images Using Hybrid GLCM-LDTP-Le-Net Feature extraction and Bi-LSTM model
2022
International Journal of Intelligent Engineering and Systems
The proposed hybrid feature extraction increases the accuracy of learned models by extracting the combined features from the input data. ...
The proposed hybrid feature extraction obtained an accuracy of 97.88 %, better when compared with the existing CNN-based models' methods that obtained accuracy of 91%. ...
Narmatha [14] developed a hybrid fuzzy brain-storm optimization algorithm for performing the classification of brain MRI images. ...
doi:10.22266/ijies2022.0430.12
fatcat:5gpvkmyvqfb4vc2juldgrrqalu
TCTAP C-175 Seal the Hole, Not the Vessel!
2019
Journal of the American College of Cardiology
In previous issue, we ran a thematic on brain storm optimization (BSO), a novel evolutionary algorithm inspired by the way humans carry out brainstorming process. ...
The other paper on ELM is by Lu et al. with the proposal of an improved weighted ELM for imbalanced data classification. They incorporated a voting scheme to eliminate classes that are not useful. ...
In previous issue, we ran a thematic on brain storm optimization (BSO), a novel evolutionary algorithm inspired by the way humans carry out brainstorming process. ...
doi:10.1016/j.jacc.2019.03.381
fatcat:ae5if24bpbea7jhnyjn3i5v434
Feature selection technique applied in Medical application by Supervised algorithm: A Review
2021
Zenodo
Feature selection is a strategy for preprocessing that determines the main features of a specific problem. ...
In this paper, a review started to describe some basic concepts related to medical applications and provide some necessary background information on feature selection and reviewed more than ten articles ...
The classification was carried out using a vector support machine with its parameters configured by an algorithm for brain storm optimization. ...
doi:10.5281/zenodo.4543647
fatcat:5osyaocsbnaavaxoen4sxjhuai
« Previous
Showing results 1 — 15 out of 5,602 results