Results 21 to 30 of about 6,479 (185)

Intelligent online process fault diagnosis through integrating Andrews function, autoencoder, and neural networks

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This paper proposes an online process fault diagnosis scheme that integrates principal component analysis, Andrews function, autoencoder, and multilayer feedforward neural network to enhance the fault diagnosis performance. Useful features are extracted from the online monitoring data by using Andrews function (also known as Andrews plot).
Shengkai Wang, Jie Zhang
wiley   +1 more source

Conditional fiducial models [PDF]

, 2017
The fiducial is not unique in general, but we prove that in a restricted class of models it is uniquely determined by the sampling distribution of the data. It depends in particular not on the choice of a data generating model.
Lindqvist, Bo H., Taraldsen, Gunnar
core   +2 more sources

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

Fuzzy sets in nonparametric Bayes regression

, 2008
A simple Bayesian approach to nonparametric regression is described using fuzzy sets and membership functions. Membership functions are interpreted as likelihood functions for the unknown regression function, so that with the help of a reference prior ...
Angers, Jean-François, Delampady, Mohan
core   +1 more source

Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges

Epilepsia Open, EarlyView.
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus, Cesar Santana‐Gomez, Ruby G. Escalante, Dominique Duncan, Pedro F. Viana, Giulia Sofia Cereda, Naoto Kuroda, Aristea S. Galanopoulou   +7 more
wiley   +1 more source

Waves of Uncertainty: Crude Oil Under Geopolitical, Economic, and ESG Turbulence

Energy Science &Engineering, EarlyView.
Dynamic copula and wavelet coherence reveal that geopolitical, economic, and sustainability uncertainties significantly shape crude oil price co‐movements. Long‐term coherence, especially post‐2015, highlights the growing role of ESG risks alongside geopolitical shocks and economic crises in global energy risk transmission.
Sana Braiek, Naif Alsagr, Aamir Aijaz Syed, Ahmed Jeribi   +3 more
wiley   +1 more source

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

Energy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan, Suresh Panchanathan, Chan Choon Kit, Elumalai Perumal Venkatesan, Nasim Hasan   +4 more
wiley   +1 more source

A fuzzy taxonomy for e-Health projects [PDF]

, 2012
Evaluating the impact of Information Technology (IT) projects represents a problematic task for policy and decision makers aiming to define roadmaps based on previous experiences.
D'Urso, Pierpaolo, De Giovanni, Livia, Spagnoletti, Paolo   +2 more
core   +1 more source

A Hybrid Fuzzy–Support Vector Machine Framework for Real‐Time Dust Detection and Thermal Mapping in Photovoltaic Panels

Energy Science &Engineering, EarlyView.
A hybrid Fuzzy–SVM framework for real‐time dust detection and thermal mapping in PV panels. ABSTRACT Dust accumulation significantly degrades the energy output of photovoltaic (PV) panels, particularly in arid and semi‐arid regions. While existing studies have separately explored image‐based dust detection, environmental modeling, and machine learning (
Debasish Sarker, S. M. Rezaul Karim, MD. Shouquat Hossain, Md. Moshaddek Hossain, Md. Monirul Kabir   +4 more
wiley   +1 more source

A fuzzy model for sensitivity analysis in real options [PDF]

, 2008
This paper adopts a promising concept of uncertainty, incorporating both stochastic processes and fuzzy theory to capture the somewhat vague and imprecise ideas the manager has about the future expected cash flows, the profitability of the project, the ...
Agliardi, Elettra, Guerra, Maria Letizia, Stefanini, Luciano   +2 more
core   +1 more source