基于自适应神经模糊推理系统(anfis)的产品销售结果预测

Dolli Sari Sinaga, A. Windarto, Rizki Alfadillah Nasution, Irfan Sudahri Damanik
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引用次数: 1

摘要

本研究旨在使未来X市场的产品销售利润最大化,损失最小化。本研究使用的数据是通过观察和访谈直接从X Market Trade获得的。X市场贸易是生产和销售食品的行业之一,在该地区和地区外销售。要处理的数据是X市场食品销售的结果,使用模糊逻辑和人工神经网络相结合的自适应神经模糊推理系统(ANFIS)方法。使用的数据是2018年至2020年的月度销售数据多达36个数据。从总共36个数据中,将其分为2种训练和测试数据分布,即90:10,共60个epoch,学习率范围为0.1 - 0.9。从研究结果来看,在90%的训练数据和10%的测试数据上获得了最高的准确率88.55%,学习率为0.6。结果表明,ANFIS方法可以应用于豆腐的销售预测。通过这项研究,期望为X市场在未来的产品销售中优化利润和减少损失提供投入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PREDICTION OF PRODUCT SALES RESULTS USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS)
This study aims to optimize profits and minimize losses from product sales at X Market has achieved in the future. The data used in this study were obtained directly from X Market Trade by observing and interviewing. X Market Tradingis one of the industries that produces and sells food products to be marketed in the region and outside the region. The data to be processed is the result of the sale of food products at X Market uses the adaptive neuro fuzzy inference system (ANFIS) method which is a combination of Fuzzy Logic and Artificial Neural Networks. The data used is monthly sales data from 2018 to 2020 as many as 36 data. From a total of 36 data, it will be divided into 2 types of training and test data distribution, namely 90:10 with a total of 60 epochs and a learning rate range of 0.1 – 0.9. From the research results obtained the highest accuracy of 88.55% on 90% training data and 10% test data with a learning rate of 0.6. It was concluded that the ANFIS method could be implemented in predicting the sales of tofu. By doing this research is expected to provide input to X Market in optimizing profits and minimizing losses from product sales in the future.
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