[HTML][HTML] A review on extreme learning machine
Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …
neural network (SLFN), which converges much faster than traditional methods and yields …
Host-based IDS: A review and open issues of an anomaly detection system in IoT
Abstract The Internet of Things (IoT) envisions a smart environment powered by connectivity
and heterogeneity where ensuring reliable services and communications across multiple …
and heterogeneity where ensuring reliable services and communications across multiple …
[HTML][HTML] A modified grey wolf optimization algorithm for an intrusion detection system
Cyber-attacks and unauthorized application usage have increased due to the extensive use
of Internet services and applications over computer networks, posing a threat to the service's …
of Internet services and applications over computer networks, posing a threat to the service's …
[HTML][HTML] Predicting breast cancer from risk factors using SVM and extra-trees-based feature selection method
Developing a prediction model from risk factors can provide an efficient method to recognize
breast cancer. Machine learning (ML) algorithms have been applied to increase the …
breast cancer. Machine learning (ML) algorithms have been applied to increase the …
[HTML][HTML] Evaluation of tree-based ensemble machine learning models in predicting stock price direction of movement
EK Ampomah, Z Qin, G Nyame - Information, 2020 - mdpi.com
Forecasting the direction and trend of stock price is an important task which helps investors
to make prudent financial decisions in the stock market. Investment in the stock market has a …
to make prudent financial decisions in the stock market. Investment in the stock market has a …
[HTML][HTML] The use of ensemble models for multiple class and binary class classification for improving intrusion detection systems
The pursuit to spot abnormal behaviors in and out of a network system is what led to a
system known as intrusion detection systems for soft computing besides many researchers …
system known as intrusion detection systems for soft computing besides many researchers …
pAtbP-EnC: identifying anti-tubercular peptides using multi-feature representation and genetic algorithm based deep ensemble model
Mycobacterium tuberculosis, a highly perilous pathogen in humans, serves as the causative
agent of tuberculosis (TB), affecting nearly 33% of the global population. With the increasing …
agent of tuberculosis (TB), affecting nearly 33% of the global population. With the increasing …
[HTML][HTML] A breast cancer risk predication and classification model with ensemble learning and big data fusion
Breast cancer is a major health issue for women all over the world. Effective care and better
patient outcomes depend on early identification and precise risk prediction. Ensemble …
patient outcomes depend on early identification and precise risk prediction. Ensemble …
Building energy performance prediction: A reliability analysis and evaluation of feature selection methods
The advancement of smart meters using evolving technologies such as the Internet of
Things (IoT) is producing more data for the training of energy prediction models. Since many …
Things (IoT) is producing more data for the training of energy prediction models. Since many …
A hierarchical intrusion detection system based on extreme learning machine and nature-inspired optimization
The surge in cyber-attacks has driven demand for robust Intrusion detection systems (IDSs)
to protect underlying data and sustain availability of network services. Detecting and …
to protect underlying data and sustain availability of network services. Detecting and …