Random forest model for forecasting vegetable prices: a case study in Nakhon Si Thammarat Province, Thailand

Q2 Computer Science

International Journal of Electrical and Computer Engineering Pub Date : 2023-10-01 DOI:10.11591/ijece.v13i5.pp5265-5272

Sopee Kaewchada, Somporn Ruang-On, U. Kuhapong, Kritaphat Songsri-in

{"title":"Random forest model for forecasting vegetable prices: a case study in Nakhon Si Thammarat Province, Thailand","authors":"Sopee Kaewchada, Somporn Ruang-On, U. Kuhapong, Kritaphat Songsri-in","doi":"10.11591/ijece.v13i5.pp5265-5272","DOIUrl":null,"url":null,"abstract":"The objectives of this research were developing a model for forecasting vegetable prices in Nakhon Si Thammarat Province using random forest and comparing the forecast results of different crops. The information used in this paper were monthly climate data and average monthly vegetable prices collected between 2011 – 2020 from Nakhon Si Thammarat meteorological station and Nakhon Si Thammarat Provincial Commercial Office, respectively. We evaluated model performance based on mean absolute percentage error (MAPE), root mean squared error (RMSE), and mean absolute error (MAE). The experimental results showed that the random forest model was able to predict the prices of vegetables, including pumpkin, eggplant, and lentils with high accuracy with MAPE values of 0.09, 0.07, and 0.15, with RMSE values of 1.82, 1.46, and 2.33, and with MAE values of 3.32, 2.15, and 5.42, respectively. The forecast model derived from this research can be beneficial for vegetable planting planning in the Pak Phanang River Basin of Nakhon Si Thammarat Province, Thailand.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Electrical and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/ijece.v13i5.pp5265-5272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Computer Science","Score":null,"Total":0}

引用次数: 0

Abstract

The objectives of this research were developing a model for forecasting vegetable prices in Nakhon Si Thammarat Province using random forest and comparing the forecast results of different crops. The information used in this paper were monthly climate data and average monthly vegetable prices collected between 2011 – 2020 from Nakhon Si Thammarat meteorological station and Nakhon Si Thammarat Provincial Commercial Office, respectively. We evaluated model performance based on mean absolute percentage error (MAPE), root mean squared error (RMSE), and mean absolute error (MAE). The experimental results showed that the random forest model was able to predict the prices of vegetables, including pumpkin, eggplant, and lentils with high accuracy with MAPE values of 0.09, 0.07, and 0.15, with RMSE values of 1.82, 1.46, and 2.33, and with MAE values of 3.32, 2.15, and 5.42, respectively. The forecast model derived from this research can be beneficial for vegetable planting planning in the Pak Phanang River Basin of Nakhon Si Thammarat Province, Thailand.

查看原文本刊更多论文

蔬菜价格预测的随机森林模型:以泰国那空西塔玛拉府为例

这项研究的目的是开发一个模型，利用随机森林预测那空西塔玛拉省的蔬菜价格，并比较不同作物的预测结果。本文使用的资料分别来自那空西他玛拉特气象站和那空西他玛拉特省商务办事处2011 - 2020年的月度气候数据和月平均蔬菜价格。我们基于平均绝对百分比误差(MAPE)、均方根误差(RMSE)和平均绝对误差(MAE)来评估模型的性能。实验结果表明，随机森林模型对南瓜、茄子和扁豆等蔬菜的价格预测精度较高，MAPE值分别为0.09、0.07和0.15,RMSE值分别为1.82、1.46和2.33,MAE值分别为3.32、2.15和5.42。该预测模型可为泰国那空泗塔玛拉府Pak Phanang河流域蔬菜种植规划提供参考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

International Journal of Electrical and Computer Engineering Computer Science-Computer Science (all)

CiteScore

4.10

自引率

0.00%

发文量

177

期刊介绍： International Journal of Electrical and Computer Engineering (IJECE) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering which covers, but not limited to, the following scope: -Electronics: Electronic Materials, Microelectronic System, Design and Implementation of Application Specific Integrated Circuits (ASIC), VLSI Design, System-on-a-Chip (SoC) and Electronic Instrumentation Using CAD Tools, digital signal & data Processing, , Biomedical Transducers and instrumentation, Medical Imaging Equipment and Techniques, Biomedical Imaging and Image Processing, Biomechanics and Rehabilitation Engineering, Biomaterials and Drug Delivery Systems; -Electrical: Electrical Engineering Materials, Electric Power Generation, Transmission and Distribution, Power Electronics, Power Quality, Power Economic, FACTS, Renewable Energy, Electric Traction, Electromagnetic Compatibility, High Voltage Insulation Technologies, High Voltage Apparatuses, Lightning Detection and Protection, Power System Analysis, SCADA, Electrical Measurements; -Telecommunication: Modulation and Signal Processing for Telecommunication, Information Theory and Coding, Antenna and Wave Propagation, Wireless and Mobile Communications, Radio Communication, Communication Electronics and Microwave, Radar Imaging, Distributed Platform, Communication Network and Systems, Telematics Services and Security Network; -Control[...] -Computer and Informatics[...]