Results 101 to 110 of about 101,601 (232)

Data‐Driven Design of Scalable Perovskite Film Fabrication via Machine Learning–Guided Processing

open access: yesCarbon Energy, EarlyView.
Considering complex process parameters and poor reproducibility in perovskite thin film fabrication, this study uses machine learning to analyze and predict high‐dimensional process variables. The Random Forest model, identified as the most effective, can effectively analyze and rapidly predict optimal process parameters from extensive data.
Hong Liu   +9 more
wiley   +1 more source

PREDICTION OF UNIT VALUE INDEX OF EXPORTS OF SITC 897 JEWELRY AND PRECIOUS GOODS GROUP IN INDONESIA

open access: yesBarekeng
Export is an international trade activity that plays an important role in the economic progress in Indonesia. One of Indonesia's leading commodities that dominate the export market is jewelry.
Grace Lucyana Koesnadi   +4 more
doaj   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos   +3 more
wiley   +1 more source

Verteilungsfragen in Deutschland: Herausforderungen der Messung und der zielgerichteten Umverteilung

open access: yesWirtschaftsdienst, 2020
Lars P. Feld   +3 more
doaj   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

open access: yesDeep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li   +4 more
wiley   +1 more source

Comparative Study of Linear Regression, SVR, and XGBoost for Stock Price Prediction After a Stock Split

open access: yesJournal of Applied Informatics and Computing
This study aims to identify the most effective regression method for predicting the closing stock price of Bank Central Asia (BBCA) following the stock split event on October 12, 2021.
Muhammad Yusuf Andrika, Majid Rahardi
doaj   +1 more source

Optimal Power Flow with Step-Voltage Regulators in Multi-Phase Distribution Networks

open access: yes, 2019
This paper develops a branch-flow based optimal power flow (OPF) problem for multi-phase distribution networks that allows for tap selection of wye, closed-delta, and open-delta step-voltage regulators (SVRs).
Bazrafshan, Mohammadhafez   +2 more
core  

AI‐Driven Precision Annealing for High Performance Fe‐Based Amorphous Alloys

open access: yesENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
The four stages of the research process are as follows: First, data is collected and a database is constructed. This is followed by feature selection and analysis, then the establishment of machine learning models, and finally formulation design and preparation.
Yichuan Tang   +13 more
wiley   +1 more source

Pharmaförderung ausschließlich aus Steuermitteln

open access: yesMonitor Versorgungsforschung
„Preise innovativer Arzneimittel in einem lernenden Gesundheitssystem“, lautet der Titel des aktuellen Gutachtens 2025 des Sachverständigenrats zur Begutachtung der Entwicklung im Gesundheitswesen und in der Pflege (SVR) – ein Thema übrigens, das der Rat
Peter Stegmaier
doaj   +1 more source

AI‐driven circular economy optimization in waste management: A review of current evidence

open access: yesEnvironmental Progress &Sustainable Energy, EarlyView.
Abstract The integration of artificial intelligence (AI) and machine learning (ML) in waste management has the potential to significantly advance circular economy objectives by enhancing efficiency, reducing waste, and optimizing resource recovery. However, realising these benefits depends on addressing significant technical, economic, and systemic ...
David Bamidele Olawade   +3 more
wiley   +1 more source

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