Marknadens största urval
Snabb leverans

Böcker av Edgar N. Sanchez

Filter
Filter
Sortera efterSortera Populära
  • av Edgar N. Sanchez, Esteban A. Hernandez-Vargas & Jorge X. Velasco-Hernandez
    1 820,-

    Mathematical Modeling, Simulations, and Artificial Intelligence for Emergent Pandemic Diseases: Lessons Learned from COVID-19 includes new research, models and simulations developed during the COVID-19 pandemic into how mathematical methods and practice can impact future response. Chapters go beyond forecasting COVID-19, bringing different scale angles and mathematical techniques (e.g., ordinary differential and difference equations, agent-based models, artificial intelligence, and complex networks) which could have potential use in modeling other emergent pandemic diseases. A major part of the book focuses on preparing the scientific community for the next pandemic, particularly the application of mathematical modeling in ecology, economics and epidemiology. Readers will benefit from learning how to apply advanced mathematical modeling to a variety of topics of practical interest, including optimal allocations of masks and vaccines but also more theoretical problems such as the evolution of viral variants.

  • av Edgar N. Sanchez & Larbi Djilali
    1 546 - 1 550,-

    This book presents advanced control techniques that use neural networks to deal with grid disturbances in the context renewable energy sources, and to enhance low-voltage ride-through capacity, which is a vital in terms of ensuring that the integration of distributed energy resources into the electrical power network.

  • av Edgar N. Sanchez, Alma Y. Alanis, Ramon Garcia-Hernandez, m.fl.
    1 870,-

  • - Control for Wind Energy
    av Edgar N. Sanchez
    2 630,-

    This comprehensive book addresses the modeling and design of controllers for the doubly fed induction generator (DFIG) used in wind energy applications. Focusing on the use of nonlinear control techniques, the text discusses the main features and advantages of the DFIG, describes key theoretical fundamentals and the DFIG mathematical model, and develops controllers using inverse optimal control, sliding modes, and neural networks. It also devises an improvement to add robustness in the presence of parametric variations, as well as details the results of real-time implementations.

Gör som tusentals andra bokälskare

Prenumerera på vårt nyhetsbrev för att få fantastiska erbjudanden och inspiration för din nästa läsning.