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From Wikipedia, the free encyclopedia

An approximation (usually represented by the symbol ≈) is an inexact representation of something that is still close enough to be useful. Although approximation is most often applied to numbers, it is also frequently applied to such things as mathematical functions, shapes, and physical laws.

Approximations may be used because incomplete information prevents use of exact representations. Many problems in physics are either too complex to solve analytically, or impossible to solve using the available analytical tools. Thus, even when the exact representation is known, an approximation may yield a sufficiently accurate solution while reducing the complexity of the problem significantly.

For instance, physicists often approximate the shape of the Earth as a sphere even though more accurate representations are possible, because many physical behaviours—e.g. gravity—are much easier to calculate for a sphere than for other shapes.

It is difficult to exactly analyze the motion of several planets orbiting a star, for example, due to the complex interactions of the planets' gravitational effects on each other, so an approximate solution is effected by performing iterations. In the first iteration, the planets' gravitational interactions are ignored, and the star is assumed to be fixed. If a more precise solution is desired, another iteration is then performed, using the positions and motions of the planets as identified in the first iteration, but adding a first-order gravity interaction from each planet on the others. This process may be repeated until a satisfactorily precise solution is obtained. The use of perturbations to correct for the errors can yield more accurate solutions. Simulations of the motions of the planets and the star also yields more accurate solutions.

As another example, in order to accelerate the convergence rate of evolutionary algorithms, fitness approximation - that leads to build model of the fitness function to choose smart search steps - is a good solution.

The type of approximation used depends on the available information, the degree of accuracy required, the sensitivity of the problem to this data, and the savings (usually in time and effort) that can be achieved by approximation.



The scientific method is carried out with a constant interaction between scientific laws (theory) and empirical measurements, which are constantly compared to one another.

The approximation also refers to using a simpler process. This model is used to make predictions easier. The most common versions of philosophy of science accept that empirical measurements are always approximations—they do not perfectly represent what is being measured. The history of science indicates that the scientific laws commonly felt to be true at any time in history are only approximations to some deeper set of laws. For example, attempting to resolve a model using outdated physical laws alone incorporates an inherent source of error, which should be corrected by approximating the quantum effects not present in these laws.

Each time a newer set of laws is proposed, it is required that in the limiting situations in which the older set of laws were tested against experiments, the newer laws are nearly identical to the older laws, to within the measurement uncertainties of the older measurements. This is the correspondence principle.


~ (informal)
=~ (plain text)

symbols representing

Approximation usually occurs when an exact form or an exact numerical number is unknown or difficult to obtain. However some known form may exist and may be able to represent the real form so that no significant deviation can be found. It also is used when a number is not rational, such as the number π, which often is shortened to 3.14, or √7 as ≈ 2.65. Numerical approximations sometimes result from using a small number of significant digits. Approximation theory is a branch of mathematics, a quantitative part of functional analysis. Diophantine approximation deals with approximation to real numbers by rational numbers. The symbol "≈" means "approximately equal to"; the Libra sign (Libra.svg) is a common alternative. Another alternative is ≒. The tilde (~) is sometimes used to signify a poor approximation (i.e. 92 ~ 100).

In plain text applications

A way of writing "approximately equal to" ("almost equal to" \ "equals approximately" \ "approximately equals") in standard internet-based text (email, comment forms, forums, message boards, et cetera) or plain text applications is =~. ≅ and ≈ are symbols that are not easy for people to enter in email, forums, etc. (no standardized keyboard entry method), and are not universally rendered correctly in web browsers (in fact, you may be seeing boxes instead of symbols right now) and are not commonly parsed correctly in web tools like commenting and forums. The Microsoft Symbol font in the Windows versions of the Microsoft Office application suite can be used to produce the "approximately equal to symbol" by holding down the Alt key (as a shift key) and typing 2248 (Office 2007) on the numeric keypad then releasing the Alt key. This method works for Word, Excel and PowerPoint and other Windows applications that can select the Symbol font. The ~ symbol is too often used to indicate some other meaning (e.g. 'NOT'), or decoratively. (Note: In HTML 4 "~" is defined as "varies with" or "similar to".)

See also

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