Mean Absolute Percentage Error

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

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 11 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

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 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

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

This paper focuses on municipal solid waste generation in city of Tehran, the most populated city in Middle East. Three methods are explored in this paper to analyze the past solid waste time-series analysis: regression, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS).

10p kelseynguyen 28-05-2020 11 0   Download

Present investigation was an attempt to study the trend of jute production in West Bengal for the period starting from 1950 to 2016. For stochastic trend estimation, a number of time series parametric regression models viz. Linear model, Quadratic model, Exponential model, Logarithmic model, Power model and Auto Regressive Integrated Moving Average (ARIMA) were employed and compared for finding out an appropriate econometric model to capture the trend of jute production of the country. Based on the performance of several goodness of fit criteria viz.

12p trinhthamhodang3 17-02-2020 27 0   Download

The study employs the Box-Jenkins Methodology to forecast South African gold sales. For a resource economy like South Africa where metals and minerals account for a high proportion of GDP and export earnings, the decline in gold sales is very disturbing. Box-Jenkins time series technique was used to perform time series analysis of monthly gold sales for the period January 2000 to June 2013 with the following steps: model identification, model estimation, diagnostic checking and forecasting. Furthermore, the prediction accuracy is tested using mean absolute percentage error (MAPE).

7p chauchaungayxua2 09-01-2020 33 0   Download

The present study aimed to develop the predictive models of average tool-workpiece interface temperature in hard turning of AISI 1060 steels by coated carbide insert. The Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were employed to predict the temperature in respect of cutting speed, feed rate and material hardness. The number and orientation of the experimental trials, conducted in both dry and high pressure coolant (HPC) nvironments, were planned using full factorial design. The temperature was measured by using the tool-work thermocouple.

10p kequaidan1 16-11-2019 10 0   Download

This study also analyses on the trending of the faculty and students to get valuable results which are accurate by applying the Mean Absolute Percentage Error (MAPE) showing low range errors. After that, this study can provide the Ministry of Vietnamese Education and Training (MOET) a good method and results to plan the education policies and resources allocation in the future.

13p praishy2 27-02-2019 35 1   Download

In the case of Taiwan, the modified models resulted in very low values of mean of absolute percentage error (MAPE) of 0.33% and 0.58%, respectively to the energy consumption and real GDP. Hence, the modified model is strongly suggested to forecast the energy intensity in Taiwan from 2012-2015.

6p girlsseek 27-02-2019 30 0   Download