Mean absolute error

Movies are a primary source of entertainment, but finding specific content can be challenging given the exponentially increasing number of movies produced each year. Recommendation systems are extremely useful for solving this problem. While various approaches exist, Collaborative Filtering (CF) is the most straightforward.

10p vialicene 02-07-2024 1 0   Download

The purpose of this study is to forecast the arrival of foreign tourists in Indonesia by using Artificial Neural Network and Holt-Winters approach esutilising the historical data from January 2011 to December 2017. From the calculation process, we found that MAPE (Mean Absolute Percentage Error) value of Artificial Neural Network and HoltWinters approaches are 5.60% and 5.43%, respectively. So it can be concluded that the HoltWinters approach is better than the Artificial Neural Network approaches in forecasting the foreign tourists arrival in Indonesia.

8p longtimenosee10 26-04-2024 1 1   Download

The purpose of this research is to find out the basic system in the supply chain, and the dynamic system of the brown sugar supply chain in Banyuwangi Regency. This research is a combination of explanatory research and causal research and uses a system dynamics approach by considering the GAP between supply and demand for local markets. Data analysis was performed using a dynamic system simulation using the powers program with a validation test through the calculation of Mean Absolute Percentage Error (MAPE).

7p longtimenosee04 06-03-2024 1 0   Download

In this paper, a short-term load forecasting model is proposed based on Long Short-Term Memory (LSTM) network combining linear regression algorithm and EVN-NLDC (National Load Dispatch Centre) data. Short-term load forecasting has an enormous impact on unit commitment, strategic power reserve for national power system and enhances the reliability of the power supply.

4p vijeff 01-12-2023 7 4   Download

This study develops and validates a short-term PV power forecasting model by using the combination of a genetic algorithm (GA) and Long Short Term Memory (LSTM). The performance of the proposed model is compared with LSTM baseline model by three errors (Root mean square error(RMSE), Mean absolute error (MAE), and Mean absolute percentage error (MAPE)) in two case studies.

6p vijeff 01-12-2023 4 3   Download

This paper develops an Artificial Neural Network (ANN) model based on 96 experimental data to forecast the dynamic modulus of asphalt concrete mixtures. The accuracy of the models was assessed using numerous performance indexes such as the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and coefficient of determination (R2).

10p visharma 20-10-2023 3 3   Download

The performance of the proposed RF model is evaluated using three statistical measurements: root mean squared error (RMSE), mean absolute error (MAE), and correlation coefficient (R). The results show that the RF model has high predictive accuracy with an RMSE of 210 cnt/h, an MAE of 121 cnt/h, and an R of 0.90. The performance of the RF model is also compared with a linear regression model and shows superior accuracy.

9p visharma 20-10-2023 8 4   Download

In recent years, there has been a surge in interest in the subject of machine learning for prediction. In this study, a temperature dataset of Vietnam’s stations is examined in order to anticipate temperature. Several forecasting models are used to accomplish this goal.

11p vipettigrew 15-03-2023 6 3   Download

To compare an autoregressive integrated moving average (ARIMA) model with a model that combines ARIMA with the Elman recurrent neural network (ARIMA-ERNN) in predicting the incidence of pertussis in mainland China. Background: The incidence of pertussis has increased rapidly in mainland China since 2016, making the disease an increasing public health threat.

11p viferrari 28-11-2022 8 2   Download

The purpose of this study is to find out the export and import turnover of Vietnam in the future time when Vietnam joins as a part in the transactions of exchanging goods with other countries all over the world. The valuation of transporting products in the future from 2020 to 2023 will be predicted by grey forecasting method with the GM (1,1) model which bases on the historical time series during the period of 2012 to 2019.

8p alucardhellsing 04-05-2022 12 1   Download

The modernization of the world has considerably reduced the prime sources of energy such as coal, diesel and gas. Thus, alternative energy sources based on renewable energy have been the main concentration nowadays to address the world’s energy demand as well as restrict global warming. Solar energy is the main source used to generate electricity through photovoltaic (PV) system. However, the output of PV power is normally intermittent.

4p vistephenhawking 26-04-2022 12 2   Download

Based on the value of mean squared error, absolute average deviation and coefficient of determination, the ANN model was found superior to DMD models in predicting the value of responses. The optimum composition of flour obtained using the DMD method was 69.44 g of PMF, 21 g of RLF and 9.56 g of MLF, whereas using the ANNGA technique, it was 68.25 g of PMF, 23.12 g of RLF and 8.63 g of MLF.

10p mudbound 10-12-2021 7 1   Download

This study compares the price predictions of the Vanguard real estate exchangetraded fund (ETF) (VNQ) using the back propagation neural network (BPNN) and autoregressive integrated moving average (ARIMA) models. The input variables for BPNN include the past 3-day closing prices, daily trading volume, MA5, MA20, the S&P 500 index, the United States (US) dollar index, volatility index, 5-year treasury yields, and 10-year treasury yields. In addition, variable reduction is based on multiple linear regression (MLR).

16p mynguyenha 21-07-2021 18 1   Download

This paper presents the biodiesel prices in Thailand with the time series decomposition method. The source of time series data comes from the energy policy and planning office, Ministry of Energy of Thailand, monthly average retail price of regular-grade biodiesel, during 2007-2016, 120 months in total. This study aims to use forecasting methods to deter biodiesel prices in Thailand over the next 20 years, from 2017 to 2036.

8p mynguyenha 21-07-2021 10 2   Download

This paper presents a new approach by combining Holt-Winters and Walk-Forward Validation methodology to forecast the maximum power demand for Ho Chi Minh City, Vietnam. The data is divided into the training and test sets in many cases. The forecast accuracy of the mean absolute error (MAE) and the mean absolute percentage error (MAPE) are used to analyze the characteristic of forecast for each day of the week.

10p tunelove 12-06-2021 16 1   Download

Forecasting solar irradiance has been an important topic and a trend in renewable energy supply share. Exact irradiance forecasting could help facilitate the solar power output prediction. Forecasting improves the planning and operation of the Photovoltaic (PV) system and the power system, then yields many economic advantages. The irradiance can be forecasted using many methods with their accuracies.

6p caygaocaolon10 05-02-2021 23 1   Download

In this paper, we simulated an eddy current sensor coil and investigated its impedance response in different scenarios using Ansys software. The experimental findings were consistent with the simulation results. For operating frequency at 180 kHz, comparison between simulation results and experimental using LCR meter and LDC1000EVM module results, the mean absolute percentage error were about 0.75% and 0.6%, respectively.

10p viv2711 27-10-2020 11 1   Download

The present study was carried out to forecast prices of paddy through univariate Seasonal Auto Regressive Integrated Moving Average (SARIMA) model. The secondary data (Time Series data) pertaining to monthly prices (Rs/q) of paddy were collected the website of Chhattisgarh State Marketing Board (Mandi) for the period from April 2009 to February 2020 have been used for the study. The SARIMA (2,1,2) (1,1,1)12 were found as the most suitable models to forecasts of paddy prices. With these models there were made forecast for 13 months, which are from March 2020 to March 2021.

7p angicungduoc6 22-07-2020 11 1   Download

The present investigation was carried out to model the trend of area and production of sugarcane in Tamil Nadu. It was obtained by using the secondary data of area and production over a period of 30 years (1984-85 to 2014-15). For this purpose, Different nonlinear models such as Logistic, Gompertz, Rational, Gaussian, Weibull, Hoerl and Sinusoidal models were employed. Levenberg-Marquardt technique was used to obtain the estimates of the unknown parameters of the nonlinear regression models.

11p angicungduoc5 14-06-2020 12 0   Download

The objective of this research is minimizing cost of production by using aggregate production planning (APP) and material flow cost accounting analysis technique (MFCA). The production process was divided into 12 processes from metal melting process to packing process. The data during past 24 months was used in five forecasting methods.

6p cleopatrahuynh 01-06-2020 13 1   Download