Mathematical Modeling MATH – 345
Instructor Lev V. Idels
Vancouver
Island University
Department of Mathematics
Fall 2011
An introduction to the application of mathematics as a tool for studying
complex systems in science and engineering. Topics include model fitting,
experimental modeling, modeling with difference and ordinary differential
equations, and optimization. (3:0:0)
Prerequisite: Min. "B" in each of MATH 100 ( or MATH
121) and MATH 101 (or MATH 122) and min. "C" in MATH 141.
Course Objective:
This course is designed to provide the students with a
fundamental understanding of how Mathematics is applied as a tool to aid in
studying complex systems in science and engineering. It will help a
student to overcome the difficult transition from basic assumptions made on a
real problem to the setting up of a model in mathematical terms. We will
introduce modern technology such as Maple and/or Matlab. When you have gone
through the course, you will have learned how to tackle real-world problems.
Instructor
Dr. Lev V. Idels
Office: Bld. 360/304
Course webpage: http://web.viu.ca/math/lev.html
E-mail: lev.idelsl@viu.ca
Office hours: Mon
11:40-2:00, Wed 11:40-2:00 or if you
need to see me outside of the announced office hours, please set up an
appointment with me, either by speaking to me before or after class, or by
sending me an email message (include "MATH 345" in the subject line,
please). To help me manage my email inbox,
please include "MATH 345" in the subject line of any email message
you send to me (without it, your message runs the risk of being deleted without
being read).
Text: A
First Course in Mathematical Modeling, Fourth Edition, by F.R. Giordano, M.D.
Weir, and W.P. Fox
|
Chapters 1-2 |
Modeling
of chemical, biological and physical systems; Dynamical systems via
difference equations |
|
Chapter 11 |
Modeling
with differential equations. |
|
Chapter 12 |
Modeling
with systems of differential equations |
|
Chapters 3-4 |
Fitting
models to data graphically and analytically. Experimental modeling. Cubic
splines and interpolation. |
|
Chapter 7 |
Discrete
optimization modeling. |
|
Chapter 13 |
Classical
optimization methods: Golden Mean, Conjugate Gradients, Constrained
Optimization. |
Grading:
|
Final
Exam |
50%
|
|
Midterm
Test |
20%
|
|
Five
Assignments with Maple |
30% |
Important Dates:
1.
Assignments (TBA) No late Assignments will be
accepted.
2.
Midterm Test (TBA)
3.
Final Exam (December
2011)