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On the transfer of adaptive predictors between different devices for both mitigation and prevention of disruptions

Nuclear fusion, 2020-05, Vol.60 (5), p.56003

2020

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Upgrades of Genetic Programming for Data Driven Modelling of Time Series

Evolutionary computation, 2023-12, Vol.31 (4), p.1-432

2023

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A hybrid physics/data-driven logic to detect, classify, and predict anomalies and disruptions in tokamak plasmas

Nuclear fusion, 2024-04, Vol.64 (4), p.46017

2024

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A systemic approach to classification for knowledge discovery with applications to the identification of boundary equations in complex systems

The Artificial intelligence review, 2022, Vol.55 (1), p.255-289

2022

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A comprehensive study of the uncertainties in bolometric tomography on JET using the maximum likelihood method

Review of scientific instruments, 2019-12, Vol.90 (12)

2019

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Data driven theory for knowledge discovery in the exact sciences with applications to thermonuclear fusion

Scientific reports, 2020-11, Vol.10 (1), p.19858-19858, Article 19858

2020

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Erratum to: On the optimal mix of Renewable Energy Sources, electrical energy storage and thermoelectric generation for the de-carbonization of the Italian electrical system

European physical journal plus, 2021-02, Vol.136 (2), p.227, Article 227

2021

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On the optimal mix of renewable energy sources, electrical energy storage and thermoelectric generation for the de-carbonization of the Italian electrical system

European physical journal plus, 2020-01, Vol.135 (1), p.72, Article 72

2020

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Application of symbolic regression to the derivation of scaling laws for tokamak energy confinement time in terms of dimensionless quantities

Nuclear fusion, 2016-02, Vol.56 (2), p.26005

2016

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Information theoretic and neural computational tools for meta-analysis of cumulative databases in the age of Big Physics experiments

Neural computing & applications, 2023, Vol.35 (1), p.469-486

2023

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Frontiers in data analysis methods: from causality detection to data driven experimental design

Plasma physics and controlled fusion, 2022-02, Vol.64 (2), p.24002

2022

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A new approach to the formulation and validation of scaling expressions for plasma confinement in tokamaks

Nuclear fusion, 2015-07, Vol.55 (7), p.73009

2015

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A maximum likelihood tomographic method applied to JET gamma ray emission during the current quench

Fusion engineering and design, 2021-07, Vol.168, p.112637, Article 112637

2021

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A statistical method for model extraction and model selection applied to the temperature scaling of the L-H transition

Plasma physics and controlled fusion, 2014-11, Vol.56 (11), p.114001-10

2014

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Non-power law scaling for access to the H-mode in tokamaks via symbolic regression

Nuclear fusion, 2013-04, Vol.53 (4), p.43001

2013

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Symbolic regression via genetic programming for data driven derivation of confinement scaling laws without any assumption on their mathematical form

Plasma physics and controlled fusion, 2015-01, Vol.57 (1), p.14008-5

2015

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UMEL: A new regression tool to identify measurement peaks in LIDAR/DIAL systems for environmental physics applications

Review of scientific instruments, 2014-06, Vol.85 (6)

2014

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Clustering based on the geodesic distance on Gaussian manifolds for the automatic classification of disruptions

Nuclear fusion, 2013-03, Vol.53 (3), p.33006

2013

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Proposal of a testing procedure to qualify ITER window assemblies and absorbing coatings exposed to high microwave stray radiation

Fusion engineering and design, 2022-08, Vol.181, p.113209, Article 113209

2022

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On the effects of missing chords and systematic errors on a new tomographic method for JET bolometry

Fusion engineering and design, 2019-09, Vol.146, p.2124-2129

2019

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An alternative approach to the determination of scaling law expressions for the L-H transition in Tokamaks utilizing classification tools instead of regression

Plasma physics and controlled fusion, 2014-11, Vol.56 (11), p.114002-12

2014

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Recent developments of the JET far-infrared interferometer-polarimeter diagnostic

Review of scientific instruments, 2010-10, Vol.81 (10), p.10D538-10D538-3

2010

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The project TELEMACO: detection, identification and concentration measurements of hazardous chemical agents

Journal of instrumentation, 2019-03, Vol.14 (3), p.C03004-C03004

2019

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A systematic investigation of radiation collapse for disruption avoidance and prevention on JET tokamak

Matter and radiation at extremes, 2023-07, Vol.8 (4), p.55-75

2023

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A statistical methodology to derive the scaling law for the H-mode power threshold using a large multi-machine database

Nuclear fusion, 2012-06, Vol.52 (6), p.63016

2012

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On the transfer of adaptive predictors between different devices for both mitigation and prevention of disruptions

Upgrades of Genetic Programming for Data Driven Modelling of Time Series

A hybrid physics/data-driven logic to detect, classify, and predict anomalies and disruptions in tokamak plasmas

A systemic approach to classification for knowledge discovery with applications to the identification of boundary equations in complex systems

A comprehensive study of the uncertainties in bolometric tomography on JET using the maximum likelihood method

Data driven theory for knowledge discovery in the exact sciences with applications to thermonuclear fusion

Erratum to: On the optimal mix of Renewable Energy Sources, electrical energy storage and thermoelectric generation for the de-carbonization of the Italian electrical system

On the optimal mix of renewable energy sources, electrical energy storage and thermoelectric generation for the de-carbonization of the Italian electrical system

Application of symbolic regression to the derivation of scaling laws for tokamak energy confinement time in terms of dimensionless quantities

Information theoretic and neural computational tools for meta-analysis of cumulative databases in the age of Big Physics experiments

Frontiers in data analysis methods: from causality detection to data driven experimental design

A new approach to the formulation and validation of scaling expressions for plasma confinement in tokamaks

A maximum likelihood tomographic method applied to JET gamma ray emission during the current quench

A statistical method for model extraction and model selection applied to the temperature scaling of the L-H transition

Non-power law scaling for access to the H-mode in tokamaks via symbolic regression

Symbolic regression via genetic programming for data driven derivation of confinement scaling laws without any assumption on their mathematical form

UMEL: A new regression tool to identify measurement peaks in LIDAR/DIAL systems for environmental physics applications

Clustering based on the geodesic distance on Gaussian manifolds for the automatic classification of disruptions

Proposal of a testing procedure to qualify ITER window assemblies and absorbing coatings exposed to high microwave stray radiation

On the effects of missing chords and systematic errors on a new tomographic method for JET bolometry

An alternative approach to the determination of scaling law expressions for the L-H transition in Tokamaks utilizing classification tools instead of regression

Recent developments of the JET far-infrared interferometer-polarimeter diagnostic

The project TELEMACO: detection, identification and concentration measurements of hazardous chemical agents

A systematic investigation of radiation collapse for disruption avoidance and prevention on JET tokamak

A statistical methodology to derive the scaling law for the H-mode power threshold using a large multi-machine database

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