An early usage of the expression “golden section”

2019 ◽  
Vol 49 ◽  
pp. 80-81 ◽  
Author(s):  
Roger Herz-Fischler
Keyword(s):  
2000 ◽  
Vol 170 (11) ◽  
pp. 1253
Author(s):  
Valerian V. Popkov ◽  
Evgenii V. Shipitsyn
Keyword(s):  

Author(s):  
Nicholas Mee

Celestial Tapestry places mathematics within a vibrant cultural and historical context, highlighting links to the visual arts and design, and broader areas of artistic creativity. Threads are woven together telling of surprising influences that have passed between the arts and mathematics. The story involves many intriguing characters: Gaston Julia, who laid the foundations for fractals and computer art while recovering in hospital after suffering serious injury in the First World War; Charles Howard, Hinton who was imprisoned for bigamy but whose books had a huge influence on twentieth-century art; Michael Scott, the Scottish necromancer who was the dedicatee of Fibonacci’s Book of Calculation, the most important medieval book of mathematics; Richard of Wallingford, the pioneer clockmaker who suffered from leprosy and who never recovered from a lightning strike on his bedchamber; Alicia Stott Boole, the Victorian housewife who amazed mathematicians with her intuition for higher-dimensional space. The book includes more than 200 colour illustrations, puzzles to engage the reader, and many remarkable tales: the secret message in Hans Holbein’s The Ambassadors; the link between Viking runes, a Milanese banking dynasty, and modern sculpture; the connection between astrology, religion, and the Apocalypse; binary numbers and the I Ching. It also explains topics on the school mathematics curriculum: algorithms; arithmetic progressions; combinations and permutations; number sequences; the axiomatic method; geometrical proof; tessellations and polyhedra, as well as many essential topics for arts and humanities students: single-point perspective; fractals; computer art; the golden section; the higher-dimensional inspiration behind modern art.


Author(s):  
Sagnik Pal ◽  
Ranjan Das

The present paper introduces an accurate numerical procedure to assess the internal thermal energy generation in an annular porous-finned heat sink from the sole assessment of surface temperature profile using the golden section search technique. All possible heat transfer modes and temperature dependence of all thermal parameters are accounted for in the present nonlinear model. At first, the direct problem is numerically solved using the Runge–Kutta method, whereas for predicting the prevailing heat generation within a given generalized fin domain an inverse method is used with the aid of the golden section search technique. After simplifications, the proposed scheme is credibly verified with other methodologies reported in the existing literature. Numerical predictions are performed under different levels of Gaussian noise from which accurate reconstructions are observed for measurement error up to 20%. The sensitivity study deciphers that the surface temperature field in itself is a strong function of the surface porosity, and the same is controlled through a joint trade-off among heat generation and other thermo-geometrical parameters. The present results acquired from the golden section search technique-assisted inverse method are proposed to be suitable for designing effective and robust porous fin heat sinks in order to deliver safe and enhanced heat transfer along with significant weight reduction with respect to the conventionally used systems. The present inverse estimation technique is proposed to be robust as it can be easily tailored to analyse all possible geometries manufactured from any material in a more accurate manner by taking into account all feasible heat transfer modes.


Helia ◽  
2001 ◽  
Vol 24 (34) ◽  
pp. 41-48
Author(s):  
I.V. Marin

SUMMARYThe aim of this work was to develop a simple method for calculating disk flower number and their density in sunflower head. The formula developed on the basis of the Golden section includes initial data of the number of smallshort rows and the number of florets in a row. It takes no more than a minute to gain initial data for calculating the formula for one head.


2020 ◽  
Vol 53 (2) ◽  
pp. 11068-11073
Author(s):  
Jingao Sun ◽  
Guanghao Su ◽  
Xianfeng Chen ◽  
Wen Yang

2020 ◽  
Vol 5 (2) ◽  
pp. 587
Author(s):  
Fong Yeng Foo ◽  
Azrina Suhaimi ◽  
Soo Kum Yoke

The conventional double exponential smoothing is a forecasting method that troubles the forecaster with a tremendous choice of its parameter, alpha. The choice of alpha would greatly influence the accuracy of prediction. In this paper, an integrated forecasting method named Golden Exponential Smoothing (GES) was proposed to solve the problem. The conventional method was reformed and interposed with golden section search such that an optimum alpha which minimizes the errors of forecasting could be identified in the algorithm training process.  Numerical simulations of four sets of times series data were employed to test the efficiency of GES model. The findings show that the GES model was self-adjusted according to the situation and converged fast in the algorithm training process. The optimum alpha, which was identified from the algorithm training stage, demonstrated good performance in the stage of Model Testing and Usage.


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