| Academic Year |
2024Year |
School/Graduate School |
School of Science |
| Lecture Code |
HB315000 |
Subject Classification |
Specialized Education |
| Subject Name |
複雑系数理 |
Subject Name
（Katakana） |
フクザツケイスウリ |
Subject Name in
English |
Theory of Complex Systems |
| Instructor |
SAITO NEN,HONDA NAOKI |
Instructor
(Katakana) |
サイトウ ネン,ホンダ ナオキ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
4th-Year, First Semester, 2Term |
| Days, Periods, and Classrooms |
(2T) Tues1-4：SCI B305 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
| lecture |
| Credits |
2.0 |
Class Hours/Week |
|
Language of Instruction |
J
:
Japanese |
| Course Level |
4
:
Undergraduate Advanced
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
01
:
Mathematics/Statistics |
| Eligible Students |
|
| Keywords |
partial differential equation, reaction-diffusion equation, stochastic process |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | Mathematics
（Knowledge and Understanding）
・Acquiring knowledge and vision on advanced theories as an extension of core theory of modern mathematics.
（Abilities and Skills）
・To learn basic knowledge, skills, and attitudes related to information. Based on them, to be able to process, output and input information, as well as to utilize information appropriately. |
|---|
Class Objectives
/Class Outline |
The lecture will provide an overview of spatio-temporal modeling methods, focusing on modeling by partial differential equations, as a method for describing complex systems such as life and natural phenomena.
|
| Class Schedule |
lesson1 Introduction
lesson2 modeling by ordinary differential equation 1
lesson3 modeling by ordinary differential equation 2
lesson4 modeling by ordinary differential equation 3
lesson5 stochastic process and partial differential equation 1 (diffusion equation)
lesson6 stochastic process and partial differential equation 2 (Fokker-Planck equation)
lesson7 stochastic process and partial differential equation 3 (examples and applications)
lesson8 stochastic process and partial differential equation 4 (examples and applications)
lesson9 reaction-diffusion equation 1 (wave propagation)
lesson10 reaction-diffusion equation 2 (Turing pattern)
lesson11 reaction-diffusion equation 3 (examples and applications)
lesson12 reaction-diffusion equation 4 (examples and applications)
lesson13 extension and prospects 1
lesson14 extension and prospects 2
lesson15 extension and prospects 3
|
Text/Reference
Books,etc. |
To be introduced in the lecture |
PC or AV used in
Class,etc. |
|
| (More Details) |
|
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
none |
| Requirements |
|
| Grading Method |
homework assignments |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |