Economic Theory and Mathematical Methods: The Intersection and Integration of Disciplines

Li, Xiangrong (Author)

ISBN 10: 9999316824 / ISBN 13: 9789999316828

Published by Eliva Press, 2024

About this Item

257 pages. 6.00x0.61x9.00 inches. In Stock.

Seller Inventory # x-9999316824

Bibliographic Details

• Title: Economic Theory and Mathematical Methods: The Intersection and Integration of Disciplines
• Publisher: Eliva Press
• Publication Date: 2024
• Language: English
• ISBN 10: 9999316824
• ISBN 13: 9789999316828
• Binding: Paperback
• Condition: Brand New
• Weight: 0.35 kilograms

About this title

Synopsis

It is well known that the combination of multiple disciplines can expand the space of academic research and enhance the comprehensiveness of academic papers, for example, the combination of finance and mathematics has created a new discipline of financial mathematics. The research on financial mathematics extends the breadth and depth of the original research. This book covers the economics, finance, mathematics, machine learning and other comprehensive multi-disciplinary academic papers, forming an interdisciplinary discipline, in which mathematical knowledge is used as a tool to solve economic problems. Specifically, this book includes “Cross-Regional Allocation of Human Capital and Sustainable Development of China’s Regional Economy—Based on the Perspective of Population Mobility; A New Hybrid PRPFR Conjugate Gradient Method for Solving Nonlinear Monotone Equations and Image Restoration Problems; A Modified Three-Term Type CD Conjugate Gradient Algorithm for Unconstrained Optimization Problems; A limited memory BFGS subspace algorithm for bound constrained nonsmooth problems; The global proof of the Polak-Ribiere-Polak algorithm under the YWL inexact line search technique; A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models; A Numerical Algorithm for the Coupled PDEs Control Problem; A modified nonmonotone BFGS algorithm for unconstrained optimization; A modified conjugate gradient algorithm with backtracking line search technique for large-scale nonlinear equations; A Conjugate Gradient Algorithm with Function Value Information and N-Step Quadratic Convergence for Unconstrained Optimization; A Limited Memory BFGS Method for Solving Large-Scale Symmetric Nonlinear Equations, and so on.” It is necessary that we should do further integration and in-depth study of the papers contained in this book. We hope this book will toss out a brick to get a jade gem and give the reader some inspiration.