Results 131 to 140 of about 13,903 (231)

RBF neural network based backstepping terminal sliding mode MPPT control technique for PV system. [PDF]

PLoS One, 2021
Khan ZA, Khan L, Ahmad S, Mumtaz S, Jafar M, Khan Q.   +5 more
europepmc   +1 more source

Using DSGE and Machine Learning to Forecast Public Debt for France

Journal of Forecasting, Volume 45, Issue 5, Page 2173-2185, August 2026.
ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos, Thierry Betti, Theophilos Papadimitriou, Amélie Barbier‐Gauchard, Periklis Gogas   +4 more
wiley   +1 more source

Multi-Sensor Fusion for Underwater Vehicle Localization by Augmentation of RBF Neural Network and Error-State Kalman Filter. [PDF]

Sensors (Basel), 2021
Shaukat N, Ali A, Javed Iqbal M, Moinuddin M, Otero P.   +4 more
europepmc   +1 more source

Identifying the Most Important Influencing Factors Based on Demographic Information, Nutrition, Physical Activity, Leisure Time, and Underlying Diseases in the Severity of Disease in COVID‐19 Patients Using Data Mining Techniques

Health Science Reports, Volume 9, Issue 8, August 2026.
ABSTRACT Background and Aims The COVID‐19 pandemic has affected millions of individuals worldwide and resulted in substantial mortality. Data mining and machine learning techniques enable the analysis of comprehensive patient data, facilitating the identification of key patterns and determinants that support clinical and preventive decision‐making ...
Noushin Mohammadifard, Nizal Sarafzadegan, Fahimeh Haghighat Doost, Jamshid Najafian, Mohammad Hossein Rouhani, Gholamreza Askari, Mohammad Sattari   +6 more
wiley   +1 more source

High-sensitivity dual-band microstrip sensor for oil-water mixture analysis with RBF neural network optimization. [PDF]

Sci Rep
Dehkalani FV, Hayati M, Horri A, Tavakoli MB.   +3 more
europepmc   +1 more source

Advanced Machine Learning Techniques for Corporate Bankruptcy Prediction: A Gradient Boosting TreeNet Approach

Intelligent Systems in Accounting, Finance and Management, Volume 33, Issue 3, September 2026.
ABSTRACT This study aims to enhance bankruptcy prediction models by employing the gradient‐boosting TreeNet algorithm. This research assesses the predictive accuracy of TreeNet in bankruptcy classification using a high‐dimensional approach. Specifically, it categorizes bankruptcy as nonbankrupt, Chapter 7, or Chapter 11 categories.
Ali Saeedi
wiley   +1 more source

Tracking control of industrial manipulator based on adaptive RBF neural network with local model approximation. [PDF]

Sci Rep
Han G, Huang C, Xiao W, Peng Y, Chen X, Mei Z.   +5 more
europepmc   +1 more source

Reliable Apparent Permeability Prediction Through Benchmarking, Stability, Uncertainty Quantification, and Explainable Machine Learning

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
ABSTRACT Apparent permeability (Papp$$ {P}_{app} $$) of a drug molecule serves as a principal indicator of drug absorption for pharmacokinetic modeling, and accurate prediction of Papp$$ {P}_{app} $$ values using machine learning would avoid time‐consuming and expensive In Vitro experiments.
Rajdeep Mondal, Rajith K. R. Rajoli, Andrew Owen, Soumitra Samanta   +3 more
wiley   +1 more source

Abrasivity behavior analysis and fuzzy stochastic prediction of weakly cemented sandstones using an improved RBF neural network for quantifying uncertainties. [PDF]

PLoS One
Yao Y, Lin J, Li X, Li Y.
europepmc   +1 more source

Adaptive and Robust Control of Diamond Quantum Sensors via Meta‐Learning

Advanced Quantum Technologies, Volume 9, Issue 8, August 2026.
Quantum Meta‐Learning: Meta‐learning frameworks address pulse transferability in NV‐center quantum sensing. By training on diverse tasks that simulate experimental variations, robust surrogate models are created that rapidly adapt to new scenarios without extensive recalibration.
Isabell Jauch, Petru Tighineanu, Patrick Tritschler, Thomas Strohm, Tino Fuchs, Fedor Jelezko   +5 more
wiley   +1 more source