Verkauf durch Sack Fachmedien

Hariharan / Han / Jafari

Machine Learning and Operational Matrix Algorithms for Nonlinear Differential Equations in Ship Dynamics

Medium: Buch
ISBN: 978-981-9254-83-5
Verlag: Springer
Erscheinungstermin: 13.01.2027
vorbestellbar, Erscheinungstermin ca. Januar 2027

This book explores analytical and numerical approximate solutions obtained by operational matrix-based methods for both classical and fractional order differential equations. An important focus of the book is to develop operational matrix methods for solving problems of ship dynamical models and fractional order ship roll motion equations arising in ocean engineering. Also, this book provides comprehensive information on the conceptual basis of operational matrix theory and its applications. It provides an essential balance between mathematical rigor and the practical applications of operational matrix theory. The book is divided into 8 chapters. The first three chapters are devoted to the mathematical foundations and basics of operational matrix algorithms. The remaining chapters provide the machine learning-based operational matrix algorithms for linear, nonlinear and fractional ship dynamical problems. The book is ideally suited as a text for graduate, postgraduate and research students in applied mathematics and computing.


Produkteigenschaften


  • Artikelnummer: 9789819254835
  • Medium: Buch
  • ISBN: 978-981-9254-83-5
  • Verlag: Springer
  • Erscheinungstermin: 13.01.2027
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2027
  • Serie: Industrial and Applied Mathematics
  • Produktform: Gebunden
  • Seiten: 135
  • Format (B x H): 155 x 235 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

Operational Matrix Algorithms using Wavelet and Orthogonal Polynomials.- An efficient machine learning based ARIMA model for the prediction of ship roll motion parameters: A bilge keel model.- A Wavelet-based ARIMA method for time series forecasting in ship roll motion models: An operational matrix of derivative approach.- A robust and reliable computational algorithm for estimating the ship roll damping parameters using hypergeometric wavelets.- An efficient polynomial approximation method for solving nonlinear oscillator equations arising in Engineering.- An efficient wavelet spectral method for the solution of ship roll motion equations using Chebyshev polynomials.- A robust approximation method for estimating ship rolls damping parameters using Hosoya polynomials.- Hybrid FWM-PINN framework for predicting Nonlinear Roll Dynamics of DTMB 5512 Ship model.- A Comparative Study on Machine Learning based Algorithms for Ship Dynamical.- Models: A PINN Approach.