A new optimized thresholding method using ant colony algorithm for MR brain image segmentation
B Khorram, M Yazdi - Journal of digital imaging, 2019 - Springer
Image segmentation is considered as one of the most fundamental tasks in image
processing applications. Segmentation of magnetic resonance (MR) brain images is also an …
processing applications. Segmentation of magnetic resonance (MR) brain images is also an …
Induction of decision trees as classification models through metaheuristics
R Rivera-Lopez, J Canul-Reich… - Swarm and Evolutionary …, 2022 - Elsevier
The induction of decision trees is a widely-used approach to build classification models that
guarantee high performance and expressiveness. Since a recursive-partitioning strategy …
guarantee high performance and expressiveness. Since a recursive-partitioning strategy …
RETRACTED ARTICLE: Optimal feature selection through a cluster-based DT learning (CDTL) in heart disease prediction
G Magesh, P Swarnalatha - Evolutionary intelligence, 2021 - Springer
In the rural side, there is the absence of centers for cardiovascular ailment. Due to this,
around 12 million people passing worldwide reported by WHO. The principal purpose of …
around 12 million people passing worldwide reported by WHO. The principal purpose of …
Swarm intelligence in data science: applications, opportunities and challenges
Abstract The Swarm Intelligence (SI) algorithms have been proved to be a comprehensive
method to solve complex optimization problems by simulating the emergence behaviors of …
method to solve complex optimization problems by simulating the emergence behaviors of …
Stability analysis and design of variable step-size P&O algorithm based on fuzzy robust tracking of MPPT for standalone/grid connected power system
This research aims to design a modified P&O algorithm for the efficient tracking of maximum
power point (MPPT) for standalone and grid-connected systems. The proposed research …
power point (MPPT) for standalone and grid-connected systems. The proposed research …
Predicting forest fire risk based on mining rules with ant-miner algorithm in cloud-rich areas
Z Zheng, Y Gao, Q Yang, B Zou, Y Xu, Y Chen… - Ecological …, 2020 - Elsevier
Annually, millions of hectares of forest lands around the world are destroyed by fires. To
minimize the fire-caused losses, more studies on the risk prediction of forest fires need to be …
minimize the fire-caused losses, more studies on the risk prediction of forest fires need to be …
Review of the machine learning methods in the classification of phishing attack
The development of computer networks today has increased rapidly. This can be seen
based on the trend of computer users around the world, whereby they need to connect their …
based on the trend of computer users around the world, whereby they need to connect their …
Dispersion ratio based decision tree model for classification
In predictive tasks like classification, Information Gain (IG) based Decision Tree is very
popularly used. However, IG method has some inherent problems like its preference …
popularly used. However, IG method has some inherent problems like its preference …
Ant-colony algorithm with a strengthened negative-feedback mechanism for constraint-satisfaction problems
K Ye, C Zhang, J Ning, X Liu - Information Sciences, 2017 - Elsevier
Abstract Ant Colony Optimization (ACO) is an efficient way to solve binary constraint-
satisfaction problems (CSPs). In recent years, new improvements have only considered …
satisfaction problems (CSPs). In recent years, new improvements have only considered …
[HTML][HTML] Literature review on big data analytics methods
IR Vanani, S Majidian - Social media and machine learning, 2019 - intechopen.com
Companies and industries are faced with a huge amount of raw data, which have
information and knowledge in their hidden layer. Also, the format, size, variety, and velocity …
information and knowledge in their hidden layer. Also, the format, size, variety, and velocity …