AIMC Topic: Commerce

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Research on the impact of industrial robot application on the status of countries in manufacturing global value chains.

PloS one
The fast growth in the installation of industrial robots has had a major impact on the comparative advantage of nations and the division of labor in global value chains in the era of smart manufacturing. Using various econometric models and panel dat...

A two-stage interval-valued carbon price forecasting model based on bivariate empirical mode decomposition and error correction.

Environmental science and pollution research international
Economic development has brought about global greenhouse gas emissions and, thus, global climate change, a common challenge worldwide and urgently needs to be addressed. Accurate carbon price forecasting plays a pivotal role in providing a reasonable...

Di-CNN: Domain-Knowledge-Informed Convolutional Neural Network for Manufacturing Quality Prediction.

Sensors (Basel, Switzerland)
In manufacturing, convolutional neural networks (CNNs) are widely used on image sensor data for data-driven process monitoring and quality prediction. However, as purely data-driven models, CNNs do not integrate physical measures or practical conside...

Modeling limit order trading with a continuous action policy for deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
Limit Orders allow buyers and sellers to set a "limit price" they are willing to accept in a trade. On the other hand, market orders allow for immediate execution at any price. Thus, market orders are susceptible to slippage, which is the additional ...

Construction and application of computerized risk assessment model for supply chain finance under technology empowerment.

PloS one
This study seeks to assist small and medium enterprises break free of the constraints of the conventional financing model and lessen the supply chain finance risks they face. First, the supply chain financial business model and credit risk are analyz...

Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS.

PloS one
For many different types of businesses, additive manufacturing has great potential for new product and process development in many different types of businesses including automotive industry. On the other hand, there are a variety of additive manufac...

Analysis of Training Deep Learning Models for PCB Defect Detection.

Sensors (Basel, Switzerland)
Recently, many companies have introduced automated defect detection methods for defect-free PCB manufacturing. In particular, deep learning-based image understanding methods are very widely used. In this study, we present an analysis of training deep...

LSTM-DGWO-Based Sentiment Analysis Framework for Analyzing Online Customer Reviews.

Computational intelligence and neuroscience
Sentiment analysis furnishes consumer concerns regarding products, enabling product enhancement development. Existing sentiment analysis using machine learning techniques is computationally intensive and less reliable. Deep learning in sentiment anal...

A Novel System to Increase Yield of Manufacturing Test of an RF Transceiver through Application of Machine Learning.

Sensors (Basel, Switzerland)
Electronic manufacturing and design companies maintain test sites for a range of products. These products are designed according to the end-user requirements. The end user requirement, then, determines which of the proof of design and manufacturing t...

Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets.

Sensors (Basel, Switzerland)
Smart manufacturing systems are considered the next generation of manufacturing applications. One important goal of the smart manufacturing system is to rapidly detect and anticipate failures to reduce maintenance cost and minimize machine downtime. ...