The golden section search is a technique for finding the extremum (minimum or maximum) of a unimodal function by successively narrowing the range of values inside which the extremum is known to exist. The technique derives its name from the fact that the algorithm maintains the function values for triples of points whose distances form a golden ratio. The algorithm is closely related to a Fibonacci search (also described below) and to a binary search.
| Property | Value |
| dbpedia-owl:thumbnail
| |
| dbpprop:abstract
|
- The golden section search is a technique for finding the extremum (minimum or maximum) of a unimodal function by successively narrowing the range of values inside which the extremum is known to exist. The technique derives its name from the fact that the algorithm maintains the function values for triples of points whose distances form a golden ratio. The algorithm is closely related to a Fibonacci search (also described below) and to a binary search. Golden section search was introduced by Kiefer (1953), and Fibonacci search by Avriel and Wilde (1966). The diagram on the right illustrates a single step in the technique for finding a minimum. The functional values of <math>f(x)</math> are on the vertical axis, and the horizontal axis is the x parameter. The value of <math>f(x)</math> has already been evaluated at the three points: <math>x_1</math>, <math>x_2</math>, and <math>x_3</math>. Since <math>f_2</math> is smaller than either <math>f_1</math> or <math>f_3</math>, it is clear that a minimum lies inside the interval from <math>x_1</math> to <math>x_3</math>. The next step in the minimization process is to "probe" the function by evaluating it at a new value of x, namely <math>x_4</math>. It is most efficient to choose <math>x_4</math> somewhere inside the largest interval, i.e. between <math>x_2</math> and <math>x_3</math>. From the diagram, it is clear that if the function yields <math>f_{4a}</math> then a minimum lies between <math>x_1</math> and <math>x_4</math> and the new triplet of points will be <math>x_1</math>, <math>x_2</math>, and <math>x_4</math>. However if the function yields the value <math>f_{4b}</math> then a minimum lies between <math>x_2</math> and <math>x_3</math>, and the new triplet of points will be <math>x_2</math>, <math>x_4</math>, and <math>x_3</math>. Thus, in either case, we can construct a new narrower search interval that is guaranteed to contain the function's minimum.
- Metoda złotego podziału - to pojęcie z zakresu optymalizacji matematycznej. Jest to numeryczna metoda optymalizacji jednowymiarowej funkcji celu. Algorytm ten może być używany przy minimalizacji kierunkowej razem z innymi metodami optymalizacji funkcji wielowymiarowych, takich jak metody gradientowe lub bezgradientowe. Innymi metodami optymalizacji jednowymiarowej są metoda dychotomii, metoda punktu środkowego, metoda Newtona.
- Метод золотого сечения — метод поиска значений действительно-значной функции на заданном отрезке. В основе метода лежит принцип деления в пропорциях золотого сечения. Наиболее широко известен как метод поиска экстремума в решении задач оптимизации.
|
| dbpprop:hasPhotoCollection
| |
| rdf:type
| |
| rdfs:comment
|
- The golden section search is a technique for finding the extremum (minimum or maximum) of a unimodal function by successively narrowing the range of values inside which the extremum is known to exist. The technique derives its name from the fact that the algorithm maintains the function values for triples of points whose distances form a golden ratio. The algorithm is closely related to a Fibonacci search (also described below) and to a binary search.
- Metoda złotego podziału - to pojęcie z zakresu optymalizacji matematycznej. Jest to numeryczna metoda optymalizacji jednowymiarowej funkcji celu. Algorytm ten może być używany przy minimalizacji kierunkowej razem z innymi metodami optymalizacji funkcji wielowymiarowych, takich jak metody gradientowe lub bezgradientowe. Innymi metodami optymalizacji jednowymiarowej są metoda dychotomii, metoda punktu środkowego, metoda Newtona.
- Метод золотого сечения — метод поиска значений действительно-значной функции на заданном отрезке. В основе метода лежит принцип деления в пропорциях золотого сечения. Наиболее широко известен как метод поиска экстремума в решении задач оптимизации.
|
| rdfs:label
|
- Golden section search
- Metoda złotego podziału
- Метод золотого сечения
|
| owl:sameAs
| |
| skos:subject
| |
| foaf:depiction
| |
| foaf:page
| |
| is dbpprop:redirect
of | |
| is owl:sameAs
of | |