A comprehensive comparative study of artificial neural network (ANN) and support vector machines (SVM) on stock forecasting
From exchanging budgetary instruments to tracking individual spending plans to detail a
business's profit, money-related organisations utilise computational innovation day by day …
business's profit, money-related organisations utilise computational innovation day by day …
Genetic algorithms in the fields of artificial intelligence and data sciences
A Sohail - Annals of Data Science, 2023 - Springer
In the fields of engineering and data sciences, the optimization problems arise on regular
basis. With the progress in the field of scientific computing and research, the optimization is …
basis. With the progress in the field of scientific computing and research, the optimization is …
Advances in big data analytics
Y Shi - Adv Big Data Anal, 2022 - Springer
Today, we are in the big data era. Big data has become a reality that no one can ignore. Big
data is our environment whenever we need to make decision. Big data is a buzz word that …
data is our environment whenever we need to make decision. Big data is a buzz word that …
An enhanced intrusion detection model based on improved kNN in WSNs
Aiming at the intrusion detection problem of the wireless sensor network (WSN), considering
the combined characteristics of the wireless sensor network, we consider setting up a …
the combined characteristics of the wireless sensor network, we consider setting up a …
A review on applications of chaotic maps in pseudo-random number generators and encryption
Because of the COVID-19 pandemic, most of the tasks have shifted to an online platform.
Sectors such as e-commerce, sensitive multi-media transfer, online banking have …
Sectors such as e-commerce, sensitive multi-media transfer, online banking have …
Student-performulator: Predicting students' academic performance at secondary and intermediate level using machine learning
S Hussain, MQ Khan - Annals of data science, 2023 - Springer
Forecasting academic performance of student has been a substantial research inquest in
the Educational Data-Mining that utilizes Machine-learning (ML) procedures to probe the …
the Educational Data-Mining that utilizes Machine-learning (ML) procedures to probe the …
An effective intrusion detection framework based on MCLP/SVM optimized by time-varying chaos particle swarm optimization
Many organizations recognize the necessities of utilizing sophisticated tools and systems to
protect their computer networks and reduce the risk of compromising their information …
protect their computer networks and reduce the risk of compromising their information …
A comprehensive study of artificial intelligence and cybersecurity on bitcoin, crypto currency and banking system
T Choithani, A Chowdhury, S Patel, P Patel… - Annals of Data …, 2024 - Springer
In recent years cryptocurrencies are emerging as a prime digital currency as an important
asset and financial system is also emerging as an important aspect. To reduce the risk of …
asset and financial system is also emerging as an important aspect. To reduce the risk of …
An improved K-means clustering algorithm towards an efficient data-driven modeling
K-means algorithm is one of the well-known unsupervised machine learning algorithms. The
algorithm typically finds out distinct non-overlap** clusters in which each point is assigned …
algorithm typically finds out distinct non-overlap** clusters in which each point is assigned …
The odd Weibull inverse topp–leone distribution with applications to COVID-19 data
EM Almetwally - Annals of Data Science, 2022 - Springer
This paper aims at defining an optimal statistical model for the COVID-19 distribution in the
United Kingdom, and Canada. A combining the inverted Topp–Leone distribution and the …
United Kingdom, and Canada. A combining the inverted Topp–Leone distribution and the …