Results 81 to 90 of about 13,903 (231)

Study on Classification and Detection of Operational Fatigue in Deep‐Well Mining Truck Drivers Based on GSWOA‐LSSVM

open access: yesSafety Science and Technology, EarlyView.
ABSTRACT Effectively detecting the operational fatigue of miners can identify safety risks in mines. As the executors of auxiliary transportation in mines, the operational fatigue status of mining truck drivers deserves particular attention and detection.
Ying Chen   +4 more
wiley   +1 more source

DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection

open access: yesIEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley   +1 more source

Research on price forecasting method of China's carbon trading market based on PSO-RBF algorithm

open access: yesSystems Science & Control Engineering, 2019
The forecasting of carbon emissions trading market price is the basis for improving risk management in the carbon trading market and strengthening the enthusiasm of market participants. This paper will apply machine learning methods to forecast the price
Yuansheng Huang   +3 more
doaj   +1 more source

Application of Intelligent Systems in CO2 Management: State of the Art and Future Prospects

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Machine learning (ML) integration is becoming increasingly popular in advancing the 4th industrial revolution, known as Industry 4.0. This review paper examines ML applications in CO2 management stages: emission, capture, and conversion. ML models, including multiple linear regression (MLR), multiple nonlinear regression (MNLR), and artificial
Muhammad Zulkefal   +7 more
wiley   +1 more source

Short‐Term Multi‐Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention‐GCN‐LSTM

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu   +4 more
wiley   +1 more source

Classification Improvement with Integration of Radial Basis Function and Multilayer Perceptron Network Architectures

open access: yesMathematics
The radial basis function architecture and the multilayer perceptron architecture are very different approaches to neural networks in theory and practice.
László Kovács
doaj   +1 more source

Using multilabel classification neural network to detect intersectional DIF with small sample sizes

open access: yesBritish Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract This study introduces InterDIFNet, a multilabel classification neural network for detecting intersectional differential item functioning (DIF) in educational and psychological assessments, with a focus on small sample sizes. Unlike traditional marginal DIF methods, which often fail to capture the effects of intersecting identities and require ...
Yale Quan, Chun Wang
wiley   +1 more source

High‐Gloss SVBRDF Capture Using Bounce Light

open access: yesComputer Graphics Forum, EarlyView.
Abstract Reflectance capture aims at the visual reproduction of an object under varying illumination. Past works differ substantially in their experimental overhead, from single‐ or few‐image approaches, that employ significant (often learned) priors at the expense of biased reconstructions, to more accurate approaches that tend to be time‐consuming ...
Tomáš Iser   +2 more
wiley   +1 more source

Maximum Power Point Tracking Control of Offshore Hydraulic Wind Turbine Based on Radial Basis Function Neural Network

open access: yesEnergies
A maximum power point tracking control strategy for an affine nonlinear constant displacement pump-variable hydraulic motor actuation system with parameter uncertainty, used within an offshore hydraulic wind turbine, is studied in this paper.
Qinwei Wang   +7 more
doaj   +1 more source

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