使用人工神经网络的论文技术指南虚拟助理

Mohammad Ovi Sanjaya, S. Bukhori, Muhammad `Ariful Furqon
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引用次数: 0

摘要

本研究的重点是寻找在学生毕业论文技术指导信息系统中实施人工神经网络(ANN)的最佳实践。机器学习模型采用了顺序模型,即 ANN 只使用 1 个输入层、1 个隐藏/密集层和 1 个输出层。数据训练过程采用了随机梯度下降法(SGD)。本研究的成果包括聊天机器人应用和使用混淆矩阵进行的模型测试。模型评估的结果是准确率为 99.49%,F-1 分数为 91%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Virtual Assistant for Thesis Technical Guide Using Artificial Neural Network
This study focuses on finding best practice for Artificial Neural Network (ANN) implementation in the information system for student’s thesis technical instructions. The machine learning model applied sequential model, it means ANN only use 1 input layer, a hidden/dense layer and 1 output layer. The Stochastic Gradient Decent (SGD) method was applied into data training process. The results of this study are chatbot applications, and model testing using the confusion matrix. The result of model evaluation are 99,49% accuracy and 91% in F-1 score.
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