Abstract Background Food flavor analysis 4.0, originating from Industry 4.0, combines
machine learning (ML) and food flavor analysis methods. Currently, food flavor analysis …

This paper presents a deep neural network (DNN) approach for induction motor fault
diagnosis. The approach utilizes sparse auto-encoder (SAE) to learn features, which …

Routine, remote, and process analysis for foodstuffs is gaining attention and can provide
more confidence for the food supply chain. A new generation of rapid methods is emerging …

In this study, a framework for Android malware detection based on permissions is presented.
This framework uses multiple linear regression methods. Application permissions, which are …

Cloud computing aimed at offering elastic resource allocation on demand to cloud
consumers. Building a cloud resource demand prediction model is a challenging task …

针对目前感应电动机故障诊断大多采用监督学习提取故障特征的现状, 提出一种将去噪编码融入
稀疏自动编码器的深度神经网络, 实现非监督学习的特征提取并用于感应电动机的故障诊断 …

Customer churn has emerged as a critical issue for Customer Relationship Management
and customer retention in the telecommunications industry, thus churn prediction is …

Hybrid system is a potential tool to deal with construction engineering and management
problems. This study proposes an optimized hybrid artificial intelligence model to integrate a …

In today's medical world, data on symptoms of patients with various diseases are so
widespread, that analysis and consideration of all factors is merely not possible by a person …

Every process is digitized in the current society. Transfer of money from one account holder
to another has become possible in seconds because of advanced technologies in …