A mini-review of machine learning in big data analytics: Applications, challenges, and prospects
The availability of digital technology in the hands of every citizenry worldwide makes an
available unprecedented massive amount of data. The capability to process these gigantic …
available unprecedented massive amount of data. The capability to process these gigantic …
Applications of artificial intelligence in engineering and manufacturing: a systematic review
Engineering and manufacturing processes and systems designs involve many challenges,
such as dynamism, chaotic behaviours, and complexity. Of late, the arrival of big data, high …
such as dynamism, chaotic behaviours, and complexity. Of late, the arrival of big data, high …
[HTML][HTML] The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction
P Chhajer, M Shah, A Kshirsagar - Decision Analytics Journal, 2022 - Elsevier
The future is unknown and uncertain, but there are ways to predict future events and reap
the rewards safely. One such opportunity is the application of machine learning and artificial …
the rewards safely. One such opportunity is the application of machine learning and artificial …
Survey of feature selection and extraction techniques for stock market prediction
In stock market forecasting, the identification of critical features that affect the performance of
machine learning (ML) models is crucial to achieve accurate stock price predictions. Several …
machine learning (ML) models is crucial to achieve accurate stock price predictions. Several …
An intrusion detection approach using ensemble support vector machine based chaos game optimization algorithm in big data platform
A Ponmalar, V Dhanakoti - Applied Soft Computing, 2022 - Elsevier
The mainstream computing technology is not efficient in managing massive data and
detecting network traffic intrusions, often including big data. The intrusions present in …
detecting network traffic intrusions, often including big data. The intrusions present in …
Predicting stock market using machine learning: best and accurate way to know future stock prices
D Sheth, M Shah - International Journal of System Assurance Engineering …, 2023 - Springer
Dissatisfaction is the first step of progress, this statement serves to be the base of using
Artifcial Intelligence in predicting stock prices. A great deal of people dreamed of predicting …
Artifcial Intelligence in predicting stock prices. A great deal of people dreamed of predicting …
A novel multi-source information-fusion predictive framework based on deep neural networks for accuracy enhancement in stock market prediction
The stock market is very unstable and volatile due to several factors such as public
sentiments, economic factors and more. Several Petabytes volumes of data are generated …
sentiments, economic factors and more. Several Petabytes volumes of data are generated …
Selection of the right undergraduate major by students using supervised learning techniques
University education has become an integral and basic part of most people preparing for
working life. However, placement of students into the appropriate university, college, or …
working life. However, placement of students into the appropriate university, college, or …
Cost-sensitive max-margin feature selection for SVM using alternated sorting method genetic algorithm
KY Aram, SS Lam, MT Khasawneh - Knowledge-Based Systems, 2023 - Elsevier
Abstract This article introduces Alternated Sorting Method Genetic Algorithm (ASMGA), a
simultaneous feature selection and model selection algorithm for Support Vector Machine …
simultaneous feature selection and model selection algorithm for Support Vector Machine …
A performance comparison of machine learning models for stock market prediction with novel investment strategy
Stock market forecasting is one of the most challenging problems in today's financial
markets. According to the efficient market hypothesis, it is almost impossible to predict the …
markets. According to the efficient market hypothesis, it is almost impossible to predict the …