Results 121 to 130 of about 45,826 (205)

Stock Closing Price and Trend Prediction with LSTM-RNN

Journal of Artificial Intelligence and Big Data
: The stock market is very volatile and hard to predict accurately due to the uncertainties affecting stock prices. However, investors and stock traders can only benefit from such models by making informed decisions about buying, holding, or investing in
Vivek Varadharajan, Nathan Smith, Dinesh Kalla, G. R. kumar, Fnu Samaah, Kiran Polimetla   +5 more
semanticscholar   +1 more source

Grindulu fault cloud radon data for earthquake magnitude prediction using machine learning [PDF]

The study investigates the potential of integrating radon gas concentration telemonitoring systems with machine learning techniques to enhance earthquake magnitude prediction.
Sunarno, Sunarno, Wijatna, Agus Budhie, Haryono, Eko, Pratama, Thomas Oka   +3 more
core   +2 more sources

Accuracy Evaluation of Multi-Factor Forecasting Methods for Customer Service Workload Prediction Under Holiday and Promotional Fluctuations: Evidence from U.S. Service Industry Data

Journal of Advanced Computing Systems
Accurate prediction of customer service workload is essential for workforce scheduling and resource allocation in the U.S. service industry. This study conducts a comparative evaluation of four forecasting approaches—Seasonal Autoregressive Integrated ...
Yajing Zhang, Minhao Li
doaj   +1 more source

SAP®’s Univariate Sales Forecasting Functionality: An Empirical Study [PDF]

, 2007
The accuracy of sales forecasts is a major determinant of inventory costs and service level driven revenues. Failure to establish future customer demand without a reasonable degree of certainty often leads to poor levels of customer service and/or high ...
Catt, Peter
core  

A novel ensemble ARIMA‐LSTM approach for evaluating COVID‐19 cases and future outbreak preparedness

Health Care Science
Background The global impact of the highly contagious COVID‐19 virus has created unprecedented challenges, significantly impacting public health and economies worldwide.
Somit Jain, Shobhit Agrawal, Eshaan Mohapatra, Kathiravan Srinivasan   +3 more
doaj   +1 more source

การทำนายประสิทธิภาพการทำงานของ JUPYTER NOTEBOOK บน JUPYTERHUBโดยใช้เทคนิคการเรียนรู้ของเครื่อง [PDF]

, 2018
MASTER OF SCIENCE (M.Sc.)วิทยาศาสตรมหาบัณฑิต (วท.ม.)In this research, machine learning was employed to predict the performance of the Jupyter notebook on the JupyterHub.

core  

Optimization of Prediction of Labor Percentage of Agricultural Information in NTB using Salp Swarm Algorithm [PDF]

: This research aims to develop an appropriate prediction model regarding the percentage of informal labor in the agricultural sector of West Nusa Tenggara (NTB) Province by utilizing the Salp Swarm Algorithm (SSA) within the framework of the third-order
Hoyali, Lailatul, Mandailina, Vera, Syaharuddin, Syaharuddin   +2 more
core  

Predictive Modeling of Enterovirus Hospital Burden Using Machine Learning and Age-Specific Surveillance Data: Operational Forecasting in Taiwan During the Postpandemic Era. [PDF]

JMIR Form Res
Kuan MM.
europepmc   +1 more source

Oil and Product Price Dynamics in International Petroleum Markets [PDF]

In this paper we investigate crude oil and products price dynamics. We present a comparison among ten price series of crude oils and fourteen price series of petroleum products, considering four distinct market areas (Mediterranean, North Western Europe,
Matteo Manera, Massimo Giovannini, Alessandro Lanza   +2 more
core  

Long-memory modeling and forecasting of monthly mean sunspot numbers for cycles 25 & 26 using ARFIMA model. [PDF]

Sci Rep
Abdel Rahman HI, Eid D.
europepmc   +1 more source