A comprehensive survey on portfolio optimization, stock price and trend prediction using particle swarm optimization
Stock market trading has been a subject of interest to investors, academicians, and
researchers. Analysis of the inherent non-linear characteristics of stock market data is a …
researchers. Analysis of the inherent non-linear characteristics of stock market data is a …
Study on the prediction of stock price based on the associated network model of LSTM
G Ding, L Qin - International Journal of Machine Learning and …, 2020 - Springer
Stock market has received widespread attention from investors. It has always been a hot
spot for investors and investment companies to grasp the change regularity of the stock …
spot for investors and investment companies to grasp the change regularity of the stock …
Decision-making for financial trading: A fusion approach of machine learning and portfolio selection
Forecasting stock returns is an exacting prospect in the context of financial time series. This
study proposes a unique decision-making model for day trading investments on the stock …
study proposes a unique decision-making model for day trading investments on the stock …
A fusion-based machine learning approach for the prediction of the onset of diabetes
A growing portfolio of research has been reported on the use of machine learning-based
architectures and models in the domain of healthcare. The development of data-driven …
architectures and models in the domain of healthcare. The development of data-driven …
[PDF][PDF] Recurrent neural networks and nonlinear prediction in support vector machines
The nonlinear regression estimation issues are solved by successful application of a novel
neural network technique termed as support vector machines (SVMs). Evaluation of …
neural network technique termed as support vector machines (SVMs). Evaluation of …
An adaptive particle swarm optimization-based hybrid long short-term memory model for stock price time series forecasting
In this paper, we presented a long short-term memory (LSTM) network and adaptive particle
swarm optimization (PSO)-based hybrid deep learning model for forecasting the stock price …
swarm optimization (PSO)-based hybrid deep learning model for forecasting the stock price …
Predicting Amazon spot prices with LSTM networks
Amazon spot instances provide preemptable computing capacity at a cost that is often
significantly lower than comparable on-demand or reserved instances. Spot instances are …
significantly lower than comparable on-demand or reserved instances. Spot instances are …
A survey of robust optimization based machine learning with special reference to support vector machines
M Singla, D Ghosh, KK Shukla - International Journal of Machine Learning …, 2020 - Springer
This paper gives an overview of developments in the field of robust optimization in machine
learning (ML) in general and Support Vector Machine (SVM)/Support Vector Regression …
learning (ML) in general and Support Vector Machine (SVM)/Support Vector Regression …
Interval forecasting of financial time series by accelerated particle swarm-optimized multi-output machine learning system
By providing a range of values rather than a point estimate, accurate interval forecasting is
critical to the success of investment decisions in exchange rate markets. This work proposes …
critical to the success of investment decisions in exchange rate markets. This work proposes …
Time series prediction methodology and ensemble model using real-world data
M Kim, S Lee, T Jeong - Electronics, 2023 - mdpi.com
Time series data analysis and forecasting have recently received considerable attention,
supporting new technology development trends for predicting load fluctuations or …
supporting new technology development trends for predicting load fluctuations or …