Math 336: Mathematical Modeling (Spring, 2020)

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Professor Youngjoon Hong:

Email: yhong2 AT sdsu DOT edu
Office hours: TTH 9:30am-10:30am at GMCS 578.
Midterm: Mar.17 (Tuesday) at the Computer Lab.


Course Links:

Useful Links:

Course Description:

Students are expected to master the basic concept of mathematical modeling in science and engineering. Students will be able to develop and understand introductory mathematical models. They will also be able to solve the models, either analytically or numerically, and interpret the modeling results using statistical methods. They will master basic principles of model error estimation, model validation by observed data, and model revision for improvement. Students will be able to write a mathematical modeling report for a specific problem from engineering and science, with high quality tables, figures and visualization.


Course Prerequisites:

Math 254 with a grade of C or better.

Course Outline:

  • Modeling change.
  • The modeling process, proportionality, and geometric similarity.
  • Model fitting.
  • Experimental modeling.
  • Simulation modeling.
  • Discrete probabilistic/optimization modeling.
  • Dynamic modeling.
  • Background of mathematical deep neural network.

    Recommended Textbooks:

      Lecture notes + (optional) A first course in mathematical modeling (3 rd edition) by Giordano, Weir, and Fox.

    Students with Disabilities:

    If you are a student with a disability and believe you will need accommodations for this class, it is your responsibility to contact Student Ability Success Center (SASC) at (619) 594-6473. To avoid any delay, please contact Student Ability Success Center as soon as possible. Please note that accommodations are not retroactive, and cannot be provided until an accommodation letter from SASC is received by the Professor.