CURRICULUM PROPOSAL FORM #3
UNIVERSITY OF WISCONSIN-WHITEWATER

NEW COURSE


Effective: Fall 2000 If adding a Graduate component to an existing course, check here ___
Course Number: * 765-445   Cross Listed Number:  
Course Title: Computer Modeling  
(limited to 65 characters)
 
15 Character Abbreviation: Comp. Modeling
25 Character Abbreviation: Computer Modeling
Sponsors: Jonathan Kane & 
Robert Siemann
  E-mail Address: kanej@mail.uww.edu
siemannb@mail.uww.edu
Department: Mathematical & Computer Sciences   College: Letters & Sciences
         
Co-sponsor:     E-mail Address:  
Department:     College:  
  * You MUST verify course numbers with Registrar's Office prior to submitting (x1211)
Other Programs Affected:  
Check if course is to meet any of the following requirements:
X None __ Writing __ Computer __ Diversity __ General Ed and Area  
Credit/Contact Hours: (per semester)
Total lab hours: 0   Total lecture hours: 48
Number of credits: 3   Total contact hours: 48
Check if course is repeatable: X No _ Yes (if yes, answer the following questions)
  • No of times in major
    No of credits in major  
  • No of times in degree
    No of credits in degree  
Enter the appropriate titles if the course is required in any of the following:
Major Title(s) Applied Mathematics & Computer Science Broadfield
Minor Title(s)   
Emphasis Title(s)  

Course justification:
The newly proposed Applied Mathematics and Computer Science Broadfield major will require some courses specifically designed to teach students how to apply computers to practical research problems which arise in mathematics and the sciences. Computer modeling is one of those areas one would expect majors in such a discipline to have. It teaches them to use some standard techniques to identify mathematical models which apply to solutions of real world problems. This course will set students from this program apart from those in other Computer Science majors in that it will give them a very practical view of how to solve real world problems rather than just giving them the ability to write a computer program already designed to solve a particular research problem.

Relationship to program assessment objectives:
This course being of an applied nature satisfies assessment objectives for mathematical and computer application courses. In particular, it meets the objectives of recognizing and applying mathematical models to the real world, developing problem solving strategies and skills, and applying technology to the solution of problems.

Budgetary impact:
There are already faculty in the Department of Mathematical and Computer Sciences with the skills to teach this course. To be able to offer this course on a regular basis will require that one extra section be taught each two years. Currently the department is searching for three new faculty with Computer Science expertise. With the filling of these positions, the new section of the course can be staffed. The new emphases in Computer Science will require adequate Computer Science laboratory facilities, but there are now plans for a new Computer Science laboratory in Hyer Hall which will be adequate to meet these needs.

Course description:
This course will introduce students to analytical techniques used to develop models of systems, and to techniques and tools of applied mathematics and computing used to solve such models. Though the topics are introductory the student will see fundamental problems and appreciate the creative and innovative methods used to solve these problems . Models discussed will be chosen from Physics, Biology, Ecology, Economics, Cognitive Studies, Manufacturing, and Engineering.

Course requisites:
Prerequisite: 760-355 and either 765-372 or 950-231

Course objectives and tentative course syllabus:
This course will introduce the student to 1) some of the analytical techniques used to develop valid models of systems, processes, and entities and 2) some of the techniques and tools of applied mathematics and applied computing used to find solutions of such models. The topics are presented at an introductory level however the student should be able to understand some of the fundamental problems and appreciate the creative and innovative methods used to solve these problems. The models discussed and developed will be chosen from a broad list of fields such as Physics, Biology, Ecology, Economics, Cognitive Studies, Manufacturing, and Engineering.

Students must have access to a package such as Mathematica on a very fast machine.

General Course Outline:

  1. Introduction to computer modeling
  2. Model analysis and design
    1. Independent variables
    2. Introduction of randomness
    3. Self consistency
    4. Stability and equilibria
    5. Sensitivity analysis
    6. Positive/negative feedback
    7. Search criteria
    8. Optimization
    9. Experimental design
  3. Finding solutions

  4.      A. Linear systems
         B. Nonlinear systems
         C. Linearized systems
         D. Self consistent solutions
         E. Search Strategies
         F. Specialized techniques
Bibliography:
Badii, R. and A.Politi (1997) Complexity (Cambridge University Press)
Gaylord, R J and P R Wellin (1995) Computer Simulations with Mathematica (Springer-Verlag NY)
Complexity Entropy and the physics of information, SFI Studies in the science of complexity, vol VIII (1990) WH Zurek, Ed( Addison-Wesley, Redwood City CA )
Vose, Michael, (1999) Simple Genetic Algorithm (MIT Press)
*Beltram,E.(1998) Mathematical Dynamic Models, (Academic Press NY )
Law, A. ,(1999) Simulation and Modeling Analysis (McGraw – Hill)
*Segel,A.(1984) Modeling Dynamic phenomena in molecular and cellular biology (Cambridge press)
*Askin,R (1993) Modeling and analysis of manufacturing systems (Wiley)
*Kobayashi,H (1978) Modeling Analysis (Addison Wesley)
*Argonne National Laboratory (1997) Modeling and simulation
Clark,E.,(1999) Model Checking (MIT press)
Gersting,J.,(1998) Mathematical Structures for Computer Science (W H Freeman)
Gaylord,R.,(1996) Modeling Nature Using Mathematica (Springer – Verlag)
Yeargers,E.,(1996) Mathematics of Biology (Birkhauser Boston)
Levine,D.,(2000) Introduction to Neural and Cognitive Modeling (Erlbaum Associates)
Odum,H.,(2000) Modeling for all Scales (academic press)
Chopard,B.,(1998) Modeling of Physical Systems (Cambridge press)
Fishwick,P.,(1995) Simulation Model Design and Execution (Prentice Hall)
Hargrove,J.,(1998) Dynamic Modeling in the Health Sciences (Springer Verlag)
De Schutter,E.,(2000) Computational Neuroscience (CRC press)
Varian,H.,(1993) Economic and Financial Modeling with Mathematica (Springer Verlag)
Warshel,A.,(1997) Computer Modeling of Chemical Reactions (Wiley)
Hannon,B.,(2000) Dynamic Modeling (Springer Verlag)
Hjorth, J.,(2000) Computer Intensive Statistical Methods (CRC press)
Hannon,B.,(1997) Modeling Dynamic Biological Systems (Springer Verlag)
O’Reilly, R.,(2000) Computational Explorations in Cognitive NeuroScience (MIT)
Zeigler,B.,(2000) Theory of Modeling and Simulation (Academic press)