Titlebook: Machine Learning for Advanced Functional Materials; Nirav Joshi,Vinod Kushvaha,Priyanka Madhushri Book 2023 The Editor(s) (if applicable)

編輯才信任

Solar Cells and Relevant Machine Learning,nce and engineering including but not limited to solar cells. It helps us to optimize materials and their photovoltaic performance for various types of solar cells through algorithms and models, which is easy, cost-efficient, and rapid compared to conventional programming methods. Although the famil

樹上結(jié)蜜糖

artifice

A Machine Learning Approach in Wearable Technologies,tential applications in different fields, ranging from healthcare to smart agriculture. In this chapter, we provide an overview of the application of machine learning algorithms to wearable technologies. After introducing the algorithms more commonly used for analyzing data from wearable devices, we

歌劇等

Potential of Machine Learning Algorithms in Material Science: Predictions in Design, Properties, ane and technology. Deep learning has attracted great interest from the research community of material science, because of its ability to statistically analyze a large collection of data. Along with the computational task, time efficient tools of machine learning have also been applied for the predict

avulsion

推遲

Perovskite-Based Materials for Photovoltaic Applications: A Machine Learning Approach,ossil fuels, which emit enormous amounts of carbon dioxide and contribute significantly to global warming. Due to global concerns about the environment and the increasing demand for energy, technological advancement in renewable energy is opening up new possibilities for its use. Even today, solar e

facetious

A Review of the High-Performance Gas Sensors Using Machine Learning, to ensure human safety in daily life and production. Machine-learning techniques have been used to successfully improve gas sensing performances of gas sensors leveraging large onsite data sets generated by them. A simple process is introduced to show the typical approach to collect the features fr

MONY

MOTTO

Contemplation of Photocatalysis Through Machine Learning, subfield of data science identified as the Machine Learning (ML). Utilization of ML could benefit the research community for various applications. Coupling of ML with a photocatalyst (PC) can accelerate the facile understanding of the relation between the structure-property-application-oriented rel

Accede