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Artificial intelligence, machine learning, deep learning, and big data techniques for the advancements of superconducting technology: a road to smarter and intelligent superconductivity

Mohammad Yazdani-Asrami

2023Superconductor Science and Technology40 citationsDOIOpen Access PDF

Abstract

Abstract The last 100 years of experience within the superconducting community have proven that addressing the challenges faced by this technology often requires incorporation of other disruptive techniques or technologies into superconductivity. Artificial intelligence (AI) methods including machine learning, deep learning, and big data techniques have emerged as highly effective tools in resolving challenges across various industries in recent decades. The concept of AI entails the development of computers that resemble human intelligence. The papers published in the focus issue, “Focus on Artificial Intelligence and Big Data for Superconductivity”, represent the cutting-edge and forefront research activities in the field of AI for superconductivity.

Topics & Concepts

Artificial intelligenceBig dataSuperconductivityDeep learningComputer scienceField (mathematics)Applications of artificial intelligenceFocus (optics)Data sciencePhysicsData miningCondensed matter physicsMathematicsOpticsPure mathematicsSuperconducting Materials and ApplicationsPhysics of Superconductivity and MagnetismSuperconductivity in MgB2 and Alloys
Artificial intelligence, machine learning, deep learning, and big data techniques for the advancements of superconducting technology: a road to smarter and intelligent superconductivity | Litcius