Autoregressive models in environmental forecasting time series: a theoretical and application review

J Kaur, KS Parmar, S Singh - Environmental Science and Pollution …, 2023 - Springer
Though globalization, industrialization, and urbanization have escalated the economic
growth of nations, these activities have played foul on the environment. Better understanding …

[HTML][HTML] A comprehensive review on multiple hybrid deep learning approaches for stock prediction

J Shah, D Vaidya, M Shah - Intelligent Systems with Applications, 2022 - Elsevier
Numerous recent studies have attempted to create efficient mechanical trading systems
through the use of machine learning approaches for stock price estimation and portfolio …

A CNN–LSTM model for gold price time-series forecasting

IE Livieris, E Pintelas, P Pintelas - Neural computing and applications, 2020 - Springer
Gold price volatilities have a significant impact on many financial activities of the world. The
development of a reliable prediction model could offer insights in gold price fluctuations …

A predictive analysis of heart rates using machine learning techniques

M Oyeleye, T Chen, S Titarenko… - International Journal of …, 2022 - mdpi.com
Heart disease, caused by low heart rate, is one of the most significant causes of mortality in
the world today. Therefore, it is critical to monitor heart health by identifying the deviation in …

Gold price forecasting using multivariate stochastic model

L Madziwa, M Pillalamarry, S Chatterjee - Resources Policy, 2022 - Elsevier
Commodities prices are pivotal to the mineral investment decision and have a considerable
impact on mining companies' financial performance and countries that depend on mineral …

[HTML][HTML] Fuzzy rule-based prediction of gold prices using news affect

P Hajek, J Novotny - Expert Systems with Applications, 2022 - Elsevier
Because of gold's value, systems for predicting its price have attracted extensive interest in
the scientific and industrial communities. Diverse artificial intelligence methods outperform …

Forecast and trend analysis of gold prices in India using auto regressive integrated moving average model

J Surendra, K Rajyalakshmi, BV Apparao… - J. Math. Comput …, 2021 - scik.org
Abstract Autoregressive Integrated Moving Average (ARIMA) is one of the powerful statistical
method to forecast the timeseries data. Forecasting plays a key role in estimating the future …

A stock price prediction model based on investor sentiment and optimized deep learning

G Mu, N Gao, Y Wang, L Dai - Ieee Access, 2023 - ieeexplore.ieee.org
Accurate prediction of stock prices can reduce investment risks and increase returns. This
paper combines the multi-source data affecting stock prices and applies sentiment analysis …

Toward smart lockdown: a novel approach for COVID-19 hotspots prediction using a deep hybrid neural network

SD Khan, L Alarabi, S Basalamah - Computers, 2020 - mdpi.com
COVID-19 caused the largest economic recession in the history by placing more than one
third of world's population in lockdown. The prolonged restrictions on economic and …

Prediction of gold price with ARIMA and SVM

D Makala, Z Li - Journal of Physics: Conference Series, 2021 - iopscience.iop.org
Gold has become more popular as well as very useful commodity in terms of investment.
Gold has been used as a national reserve for many years, and that makes it very crucial in …