Results 91 to 100 of about 34,984 (114)
Ekonometria, 2020 This paper presents a proposition to utilize flexible neural network architecture called Deep Hybrid Collaborative Filtering with Content (DHCF) as a product recommendation engine.
Filip Wójcik, Michał Górnik
doaj
A novel ensemble ARIMA‐LSTM approach for evaluating COVID‐19 cases and future outbreak preparedness
Health Care ScienceBackground The global impact of the highly contagious COVID‐19 virus has created unprecedented challenges, significantly impacting public health and economies worldwide.
Somit Jain +3 more
doaj +1 more source
Another Look at Measures of Forecast Accuracy [PDF]
We discuss and compare measures of accuracy of univariate time series forecasts. The methods used in the M-competition and the M3-competition, and many of the measures recommended by previous authors on this topic, are found to be inadequate, and many of
Anne B. Koehler, Rob J. Hyndman
core
Forecasting telecommunications data with linear models [PDF]
For telecommunication companies to successfully manage their business, companies rely on mapping future trends and usage patterns. However, the evolution of telecommunications technology and systems in the provision of services renders imperfections in ...
Madden, Gary G, Tan, Joachim
core +1 more source
Forecasting international bandwidth capacity using linear and ANN methods [PDF]
An artificial neural network (ANN) can improve forecasts through pattern recognition of historical data. This article evaluates the reliability of ANN methods, as opposed to simple extrapolation techniques, to forecast Internet bandwidth index data that ...
Madden, Gary G, Tan, Joachim
core +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
International Advances in Economic Research, 2009
Commonly used Mean Absolute Percentage Errors (MAPE) and the authors’ revised Mean Absolute Percentage Errors (RMAPE) are applied to measure the forecasting accuracy from different Moving Average Methods for independent time series. Simulation results show that both MAPE and RMAPE can only provide sensitive forecasting accuracy measurements on Moving ...
Louie Ren, Yong Glasure
openaire +3 more sources
Commonly used Mean Absolute Percentage Errors (MAPE) and the authors’ revised Mean Absolute Percentage Errors (RMAPE) are applied to measure the forecasting accuracy from different Moving Average Methods for independent time series. Simulation results show that both MAPE and RMAPE can only provide sensitive forecasting accuracy measurements on Moving ...
Louie Ren, Yong Glasure
openaire +3 more sources
Industry Xplore, 2023
The plastic resin coloring industry has a very important role in the molder supply chain. Materials must be imported from abroad with a long enough lead time, so material purchases are made based on the forecast provided by the molder. The constraints that occur are forecast inaccuracies which result in an increase in inventory level of material and a ...
Dwi Irwati, null Ade Nurul Hidayat
openaire +1 more source
The plastic resin coloring industry has a very important role in the molder supply chain. Materials must be imported from abroad with a long enough lead time, so material purchases are made based on the forecast provided by the molder. The constraints that occur are forecast inaccuracies which result in an increase in inventory level of material and a ...
Dwi Irwati, null Ade Nurul Hidayat
openaire +1 more source
Mean Absolute Percentage Error for regression models
Neurocomputing, 2016Benedicte Le Grand, Fabrice Rossi
exaly