수학적 모델

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위키데이터

• ID : Q486902

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1. The model serves as the hypothesis; simulation and experiment serve to test it.
2. Thus, the very existence of a model should eventually lead to its obsolescence.
3. Accepting this latter premise for the moment, how can general systems theory and more specifically, systems concepts aid our ability to model soil development?
4. Not all of the properties of systems outlined in Table 3.3 are necessarily going to be used in the construction of every soil-genesis model.
5. We begin by presenting the definitions of (biological) system and model.
6. Particular attention is given to the meaning of mathematical model within the context of biology.
7. For our purposes here, a model is a conceptual or mathematical representation of a system that serves to understand and quantify it.
8. A model is always a simplified representation of the reference system, which the scientist wishes to understand and quantify.
9. An application example of our methodology such as hospital beds’ management is presented in this paper to show the effectiveness of our mathematical model.
10. A mathematical model is a description of a system using mathematical concepts and language.
11. The process of developing a mathematical model is termed mathematical modeling.
12. These and other types of models can overlap, with a given model involving a variety of abstract structures.
13. In many cases, the quality of a scientific field depends on how well the mathematical models developed on the theoretical side agree with results of repeatable experiments.
14. Are there limiting cases where the model simplifies?
15. Try to have a simple working model (with report) after 1/3 of the total time planned for the task.
16. Also, importantly, the birational model may provide an upper bound of N(t), and hence it is preferable to the rational one.
17. On the other hand, the birational model requires data for several more additional days.
18. This model involves six ordinary differential equations (ODEs) specified by nine parameters.
19. However, the long series of existing data of the epidemics of Italy, Spain, France and Germany show that the logistic model does not provide accurate predictions.
20. We develop a mathematical model to present the dynamical behavior of COVID-19 infection by incorporating isolation class.
21. First, the formulation of model is proposed; then, positivity of the model is discussed.
22. The local stability and global stability of proposed model are presented, which depended on the basic reproductive.
23. For the numerical solution of the proposed model, the nonstandard finite difference (NSFD) scheme and Runge-Kutta fourth order method are used.
24. Practice 4 sets forth the notion that students should be able to "model with mathematics.
25. For example, the Nobel Memorial Prize winning economist Robert Solow developed a mathematical model using a differential equation approach for understanding economic growth.
26. There are many phrases in which model appears in conjunction with other words.
27. We hear of model homes, model railroads, and model planes.
28. it is explained how to analyze a real problem arising from science or engineering and how to best describe it through a mathematical model.
29. We simulate the model (1)-(18) in a rectangular domain Ω={(x,y),0≤x≤1,0≤y≤1}.
30. Figure 2 shows the average density of all the 18 variables of the model over a period of 10 years.
31. 2, the steady states are approximately the same as those that we assumed in estimating some of the model parameters.
32. We shall apply our model to determine how this TNF- α inhibitor affects AD patients.
33. Developing a mathematical model is really just the start of a research project.
34. Predictions obtained from any mathematical model need to be studied by experts in order to verify whether the model is a valid and accurate representation of the real-world problem of interest.
35. In the model, it was assumed that BMP is produced on the dorsal side of the embryo, Sog is produced on the ventral side, Sog inhibits BMP, and BMP and Sog interact to form the BMP–Sog complex.
36. Possible non-linear interactions between morphogens resulting in gradient scaling have recently been addressed in a framework of the expansion–repression model (Ben-Zvi & Barkai 2010).
37. In this model, one morphogen (‘repressor’) reduces the production rate of another morphogen (‘expander’), which, in turn, reduces the degradation rate of the repressor.
38. This model is indeed capable of reproducing the scaling of a morphogen, although the biological interpretation of particular kinetics used in the model is neither simple nor intuitive.
39. In this paper, we propose a mathematical model and perform computational simulations of the three-dimensional honeycomb formation using the immersed boundary method (IBM)5,6,7.
40. (2) use a mathematical model to study the impact and burden of COVID-19 across a wide range of socioeconomic and demographic settings, with a focus on low- and middle-income countries (LMICs).
41. The amount of mechanistic detail included in such a model depends on its aims.
42. Using mathematical methods to understand and model crime is a recent idea that has drawn considerable attention from researchers during the last five years.
43. We propose a more detailed form of this model that allows for two distinct criminal types associated with major and minor crime.
44. Additionally, we examine a stochastic variant of the model that represents more realistically the ‘generation’ of new criminals.
45. A preliminary statistical analysis of the data also supports the model's potential to describe crime.
46. At first glance there is nothing to model, because there was no change in production.
47. By comparing this to the weather on each day they can make a mathematical model of sales versus weather.
48. In the model, we allow mutations to occur in any order, leading to a complex network of premalignant mutational genotypes on the way to colorectal cancer.
49. We parameterize the model using experimentally measured parameter values, many of them only recently available, and compare its predictions to epidemiological data on colorectal cancer incidence.
50. The steps required for creating a mathematical model are comparable to the phases used for the scientific method.
51. Many equations are often put into a model to predict an outcome.
52. The prediction phase uses the model designed to predict what will happen in a yet-to-be-conducted experiment or an anticipated set of events in the real world.
53. Most scientists and engineers conduct experiments rather than create models, which means that they collect observations and convert those observations into a mathematical model.
54. The model proposed below shows that, under plausible assumptions, claims #1 and #2 are compatible.
55. The core of the model lies in two key assumptions, namely the second law –to be discussed in A2 below– and the long-term planning of a couple's relationship –plausibly sustained by claim #2 above.
56. Both partners share the same traits according to the model specifications below.
57. This assumption implies that the parameters, variables and utility structure defined in the model will all refer to the couple, as formed by two similar individuals.
58. You will learn to analyze your chosen problem, formulate it as a mathematical model (containing ordinary differential equations), solve the equations in the model, and validate your results.
59. If needed, you can refine or improve your model, based on your first results.
60. Young and her collaborators have been building their model by incorporating one basic element of vision at a time.
61. Previous efforts to model human vision made wishful assumptions about the architecture of the visual cortex.
62. “I think their model is an improvement in that it’s really founded on the real brain anatomy.
63. Young, Shapley and Chariker are not the first to try and answer that question with a mathematical model.
64. An early mathematical model was formed for the psychology of perception.
65. If you were going to model population growth, what factors or variables would you want to include?
66. Stella assumes that all models involve time, and we choose Stella as our model-creating tool.
67. So, we have a very simple model that we can compare to reality.
68. Choose Top of page ABSTRACT I.INTRODUCTION << II.THE MODEL AND RELATIVI...
69. We attempt to suggest a classical model for electron by studying the requirements of quantum mechanics, relativity and electrodynamics.
70. We attempt to suggest a classical model for electron by studying the requirements ofrelativity and electrodynamics.
71. We have generated a model called the Catter-Anticatter model.

메타데이터

위키데이터

• ID : Q486902

Spacy 패턴 목록

• [{'LOWER': 'mathematical'}, {'LEMMA': 'model'}]
• [{'LOWER': 'theoretical'}, {'LEMMA': 'model'}]
• [{'LEMMA': 'model'}]
• [{'LOWER': 'theoretical'}, {'LEMMA': 'model'}]
• [{'LOWER': 'models'}, {'OP': '*'}, {'LEMMA': 'theoretical'}]