Atnaujinkite slapukų nuostatas

El. knyga: Sustainable Materials: The Role of Artificial Intelligence and Machine Learning

Edited by (Politecnico di Milano, Italy), Edited by (University of Kentucky, USA), Edited by (Symbiosis International (Deemed) Uni, India)
  • Formatas: 214 pages
  • Išleidimo metai: 25-Oct-2024
  • Leidėjas: CRC Press
  • Kalba: eng
  • ISBN-13: 9781040154267
Kitos knygos pagal šią temą:
Sustainable Materials: The Role of Artificial Intelligence and Machine LearningDidesnis paveikslėlis

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

The book explores the use of AI and ML techniques for the design, characterization, and development of prediction analysis of sustainable polymer composites.



The self-learning ability of machine learning algorithms makes the investigations more accurate and accommodates all the complex requirements. Development in neural codes can accommodate the data in all the forms such as numerical values as well as images. The techniques also review the sustainability, life-span, the energy consumption in production polymer, etc. This book addresses the design, characterization, and development of prediction analysis of sustainable polymer composites using machine learning algorithms.

Preface. Artificial Intelligence in Material Science. Data Driven Artificial Intelligence Based Approach for the Determination of Structural Stress Distribution in ASTM D3039 Tensile Specimens of Carbon-Epoxy and Kevlar-Epoxy Based Composite Materials. Image Segmentation for Evaluating the Microstructure Features obtained from Magnesium Composites Processed through Squeeze Casting. Experimental Investigation of Bagasse Ash in Concrete Material. Computational Material Science for Cheminformatics Feature Descriptive Language (CFDL) with Categorical Data. Explicit Dynamic Crash Analysis of a Car using a Metal, Composite Material and an Alloy. Optimizing Friction Stir Spot Welded ABS Weld Strength using JAYA and Cohort Intelligence Algorithm. Supervised Machine Learning Based Classification of Dimensional Deviation of FDM 3D Printed Samples. Polymer Composite Flexural Strength Estimation using K-Nearest Neighbouring Classification Algorithm. Supervised Machine Learning Based Classification of Surface Roughness of Fused Deposition Modeling3D Printed Samples. Polymer Composite Impact Strength Estimation using K-Nearest Neighbouring Classification Algorithm. Index.

Akshansh Mishra is pursuing a Master's in Materials Engineering and Nanotechnology at Politecnico Di Milano, Milan, Italy. He works on the application of Artificial Intelligence-based algorithms in the Manufacturing and Materials sectors. His main research interests are Cognitive Computing, Advanced Manufacturing, Explainable Artificial Intelligence (XAI), Machine Learning, Natural Language Processing, Nature-based optimization algorithms, and Composite Materials.

Vijaykumar S Jatti is an Associate Professor at Symbiosis Institute of Technology, Pune, India. His main research interests are Machine Learning, Mechanical Design, Material Science, Conventional & Non-Conventional Machining Processes, Additive Manufacturing, and Bio-Materials (Metals, Ceramics and Polymers). He has several publications in WoS and Scopus indexed journals. He has received 18 awards in academics & research works.

Shivangi Paliwal is pursuing a Ph.D. in Mechanical Engineering, at the University of Kentucky, USA. Before joining the University of Kentucky, she worked as a Junior Research Fellow at the Indian Institute of Technology, Mumbai, India. Her research work integrates experimental and numerical simulation techniques to leverage the potential of additive manufacturing. Her research work reviews sustainability through the use of non-traditional machining and surface engineering.
Daugiau apie elektronines knygas Daugiau apie elektronines knygas
Pastovi nuoroda: https://www.kriso.lt/db/97810401542672e.html
Raktažodžiai: