A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai +8 more
wiley +1 more source
Empirical analysis of the correlation between China's Macroeconomic Market and Crude Oil Market based on mixed-frequency group factor model. [PDF]
Zhao J, Yin J.
europepmc +1 more source
The Effect of K-IFRS Adoption on The Persistence and Market Pricing of Asset Impairment Loss
Hyeri Kim, Jung-Kyo Kim
openalex +1 more source
Digital Agriculture: Past, Present, and Future
Digital agriculture integrates Internet of Things, artificial intelligence, and blockchain to enhance efficiency and sustainability in farming. This review outlines its evolution, current applications, and future directions, highlighting both technological advances and key challenges for global implementation.
Xiaoding Wang +3 more
wiley +1 more source
A multi-criteria approach to ESG-based portfolio optimization incorporating historical performance, forward-looking insights, and credibilistic CVaR: a case study on the DJIA. [PDF]
Taheripour E, Sadjadi SJ, Amiri B.
europepmc +1 more source
Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder
The overlapping and imbalanced data in classification present key challenges. Class‐separable extreme learning machine auto‐encoding (CS‐ELM‐AE) is proposed, which is an enhancement of ELM‐AE that better handles overlapping data by clustering points from the same class together. Applying oversampling addresses imbalanced data.
Ekkarat Boonchieng, Wanchaloem Nadda
wiley +1 more source
The impact of banking uncertainty on firm investment: A look into intangible assets. [PDF]
Huynh J, Phan TMH.
europepmc +1 more source
Emerging Market Crises: An Asset Markets Perspective
Ricardo J. Caballero +1 more
openalex +1 more source
Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios +4 more
wiley +1 more source

