Machine Learning and Optimization for Engineering Design / / edited by Apoorva S. Shastri, Kailash Shaw, Mangal Singh
(Visualizza in formato marc)
(Visualizza in BIBFRAME)
| Autore: |
Shastri Apoorva S
|
| Titolo: |
Machine Learning and Optimization for Engineering Design / / edited by Apoorva S. Shastri, Kailash Shaw, Mangal Singh
|
| Pubblicazione: | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Edizione: | 1st ed. 2023. |
| Descrizione fisica: | 1 online resource (175 pages) |
| Disciplina: | 006.31 |
| Soggetto topico: | Machine learning |
| Engineering design | |
| Mathematical optimization | |
| Machine Learning | |
| Engineering Design | |
| Optimization | |
| Altri autori: |
ShawKailash
SinghMangal
|
| Nota di contenuto: | Chapter 1: Development of Smart Home System Based on IoT Using a Wearable EEG -- Chapter 2: Design of Intelligent ICT Irrigation System using Crop Growth Big Data Analysis -- Chapter 3: LRBC-E: A Structurally Enhanced LRBC-Based Block Cipher for Securing Extremely Contraind IoT Devices -- Chapter 4: OpenCV and MQTT based Intelligent Traffic Management System -- Chapter 5: A Machine Learning Model for Student's Academic Success Prediction. |
| Sommario/riassunto: | This book aims to provide a collection of state-of-the-art scientific and technical research papers related to machine learning-based algorithms in the field of optimization and engineering design. The theoretical and practical development for numerous engineering applications such as smart homes, ICT-based irrigation systems, academic success prediction, future agro-industry for crop production, disease classification in plants, dental problems and solutions, loan eligibility processing, etc., and their implementation with several case studies and literature reviews are included as self-contained chapters. Additionally, the book intends to highlight the importance of study and effectiveness in addressing the time and space complexity of problems and enhancing accuracy, analysis, and validations for different practical applications by acknowledging the state-of-the-art literature survey. The book targets a larger audience by exploring multidisciplinary research directions such as computer vision, machine learning, artificial intelligence, modified/newly developed machine learning algorithms, etc., to enhance engineering design applications for society. State-of-the-art research work with illustrations and exercises along with pseudo-code has been provided here. |
| Titolo autorizzato: | Machine Learning and Optimization for Engineering Design |
| ISBN: | 9789819974566 |
| 9819974569 | |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910799232803321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |
Serie:
Engineering Optimization: Methods and Applications, . 2731-4057