My question is relatively simple: what introductory textbooks on mathematical modeling exist out there that require only a background in calculus and linear algebra (but do not require that the reader has attended a course in differential equations per se)?
The only two such textbooks that I know of are Kai Velten's "Mathematical Modeling and Simulation" and Giordano et al's "A First Course in Mathematical Modeling". Giordano is great at building intuition but is outrageously expensive, and Velten - though being a wonderful book - sometimes approaches topics too abstractly given his intended audience or, rather, fails to appropriately expound on certain abstract definitions.
There is the fantastic book 'Mathematical Modeling' by Ecke, Garcke and Knabner. It just came out two weeks ago in English (before it was published in German). We used it in a course on mathematical modeling in university and there was no prerequisite on ODEs (but of course it helps and I'd recommend that you have an ODE book as a reference). The table of content is as follows:
This book is used as the text for a freshman level applied mathematics course at my university. It is very readable and requires no background in calculus or linear algebra. It starts with difference equation, which I believe is probably the best place to start for modeling in general. The aim is toward biological processes, but the technique provided is applicable to other areas. In fact, it builds up to some major tools like Markov model and has additional computation component to it. The explanation is intuitive. You will find it to be a great place to start.
An introduction to the application of mathematics as a tool for studyingcomplex systems in science and engineering. Topics include model fitting,experimental modeling, modeling with difference and ordinary differentialequations, and optimization. (3:0:0)
This course is designed to provide the students with afundamental understanding of how Mathematics is applied as a tool to aid instudying complex systems in science and engineering. It will help astudent to overcome the difficult transition from basic assumptions made on areal problem to the setting up of a model in mathematical terms. We willintroduce modern technology such as Maple and/or Matlab. When you have gonethrough the course, you will have learned how to tackle real-world problems.
To see a (partial) list of Math PhDs along with thesis titles and advisors for me, WSU Math, and all who have up-to-date entries, check out the Mathematics Genealogy Project. It's amusing to explore.
Office hours: TTh 2:30-3:30 PM, 348 Jabara Hall, ext 3974PHYS 623 Advanced Mechanics, TR 4:00-5:20 PM, Physics seminar room next to Physics office, Jabara Hall basement.MATH 852 Numerical PDEs, JB 335. Fall 2013 Schedule Office hours: afternoons, tbd. I will be interim Director of Physics this Fall, so I may be found either in my math office JB 348 or in the Physics office JB 046.More information will be posted on the following courses soon. Interested students may contact me by email, phone, or in person.MATH 553 Mathematical Models, TR 4:00-5:15 PM, JB 372. The main text will be Mathematics and Climate, by Hans Kaper and Hans Engler. The text is not due to be published by SIAM until Sept or Oct., but I will have a preliminary copy and my notes and background material to get started with. Here is and link to some information on the text, including the Table of Contents. There is more than enough material for the semester. Realistically, we may try to cover the first 8 or 10 chapters with selected topics and projects chosen from the remaining chapters, according to our interests. Math and physics background will be provided as needed. We hope to have some related talks in the Physics Seminar, below. More info. will be posted soon. PHYS 801E Selected Topics, MW 7:05-8:20 PM, JB 021. Topics to be determined, but most likely elements of quantum field theory Shrednicki's book and Peskin and Schroeder's book.Physics 600B/807 - Physics Seminar, W, 2:00-2:50 PM, JB 128. Features talks by local and outside speakers (as usual). This semester we hope to have some speakers to talk about climate modeling.Seminars: Possibly an informal seminar on numerical conformal mapping and Riemann-Hilbert problems for multiply connected domains tentatively TR, 5:35-6:50.
The PhD Course in Engineering of Technological Innovation offers advanced training to carry out research in the field of industrial engineering and technological innovation, with particular reference to Industry 4.0 technologies.
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Component 2 of Mission 1 aims to strengthen the competitiveness of the production system by enhancing its rate of digitization, technological innovation and internationalization through a series of complementary interventions. It aims to foster the digital transition and innovation of the production system by encouraging investment in advanced technologies, research and innovation. Realize investment in ultrafast 5G fiber optic connections. Strengthen participation in the development of the space economy and Earth observation systems for monitoring territories. Promote the development and competitiveness of Italian companies also in international markets, including through innovative financial instruments.
The Consiglio Nazionale delle Richerche (National Research Council - CNR) is a national public research organization with multidisciplinary expertise, supervised by the Ministry of University and Research (MUR). Founded in 1923, it has the task of carrying out scientific research projects in the main fields of knowledge and applying their results for the development of the country, promoting innovation, internationalization of the "research system" and fostering the competitiveness of the industrial system. Every day, the CNR faces the challenges of our time in multiple areas: human and planetary health, environment and energy, food and sustainable agriculture, transport and production systems, ICT, new materials, sensors and aerospace. Also human sciences and cultural heritage protection, social sciences, bioethics, quantum sciences and technologies, artificial intelligence, and enabling technologies.
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