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相关概念视频

Trigonometric Fourier series01:17

Trigonometric Fourier series

166
Fourier series is a foundational mathematical technique that decomposes periodic functions into an infinite series of sinusoidal harmonics. This method enables the representation of complex periodic signals as sums of simple sine and cosine functions, facilitating their analysis and interpretation in various fields, including signal processing, acoustics, and electrical engineering.
The trigonometric Fourier series specifically expresses a periodic function with a defined period T using sine...
166
Graphical and Analytic Representation of Sinusoids01:20

Graphical and Analytic Representation of Sinusoids

347
Analyzing two sinusoidal voltages with equal amplitude and period but different phases on an oscilloscope, an instrument used to display and analyze waveforms, involves a three-step process.
The first step is measuring the peak-to-peak value, which is twice the amplitude of the sinusoid. This provides information about the maximum voltage swing of the waveform.
Secondly, the period and angular frequency are determined. The period is the time taken for one complete cycle of the waveform, while...
347
Direction Cosines of a Vector01:29

Direction Cosines of a Vector

394
Direction cosines, which help describe the orientation of a vector with respect to the coordinate axes, are an essential concept in the field of vector calculus. Consider vector A that is expressed in terms of the Cartesian vector form using i, j, and k unit vectors. The magnitude of vector A is defined as the square root of the sum of the squares of its components. The direction of this vector with respect to the x, y, and z axes is defined by the coordinate direction angles α, β,...
394
Rectangular and Triangular Pulse Function01:19

Rectangular and Triangular Pulse Function

498
The unit rectangular pulse function is mathematically represented by a rectangular function centered at the origin with a height of one unit. This function is defined by two parameters: T, which specifies the center location of the pulse along the time axis, and τ, which determines the pulse duration.
For example, consider a rectangular pulse with a 5V amplitude, a 3-second duration, and centered at t=2 seconds. This pulse can be expressed using the rectangular function, written as,
498
Basic signals of Fourier Transform01:07

Basic signals of Fourier Transform

450
The Fourier Transform is a pivotal mathematical tool in signal processing, enabling the transformation of time-domain signals into their frequency-domain representations. Among the numerous elements within this domain, certain functions like the sinc function, delta function, and exponential signals hold significant importance due to their unique properties and implications.
The sinc function, defined as sinc(x) = sin(πx)/(πx), is particularly notable for its symmetry and behavior at...
450
Design Example: Traverse Angle Computations01:25

Design Example: Traverse Angle Computations

36
Traverse angle computations are a critical component of surveying, used to compute the internal angles within a closed traverse. A traverse consists of a series of connected lines forming a closed loop, often used for land boundary delineation or mapping. Calculating the internal angles ensures accuracy in the traverse geometry and is essential for checking survey data integrity.The process begins with known azimuths and bearings of the traverse sides. Internal angles at each vertex are...
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相关实验视频

Updated: May 13, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
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基于三角形的正弦共弦算法用于全球搜索和特征选择.

Jiacong Liu1, Chunguang Bi2, Huiling Chen3

  • 1College of Information Technology, Jilin Agricultural University, Changchun, 130118, China.

Scientific reports
|April 15, 2025
PubMed
概括
此摘要是机器生成的。

一个新的优化算法,TTOSCA,通过三角优化和盗窃机制增强了正弦共弦算法 (SCA). TTOSCA及其二进制变体BTTOSCA在复杂的优化和特征选择任务中显示出更高的精度和融合.

关键词:
功能选择 功能选择全球优化全球优化sinus 和 cosine 的算法团结情报团队的人群.

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科学领域:

  • 计算智能是一种计算智能.
  • 优化算法 优化算法
  • 机器学习 机器学习

背景情况:

  • 弦坐标算法 (SCA) 是一个基于人口的元启发式算法.
  • 在平衡勘探和开采方面,SCA面临着挑战,特别是在高维空间,导致缓慢的融合和精度降低.

研究的目的:

  • 引入一种具有改进的优化能力的新型增强的正弦共弦算法 (TTOSCA).
  • 开发和评估二进制变体 (BTTOSCA) 用于离散优化问题,如特征选择.

主要方法:

  • 通过将三角优化 (TO) 策略和盗窃机制 (TM) 整合到SCA中,提出了TTOSCA.
  • 使用威尔科克森签名等级测试对IEEE CEC2017基准函数的27个算法进行了TTOSCA评估.
  • 评估了BTTOSCA对17个UCI数据集进行特征选择,包括医学和基因数据.

主要成果:

  • 与现有的算法相比,TTOSCA在精度和合速度方面取得了显著的改进.
  • 在特征选择中,BTTOSCA有效地平衡了勘探和开发.
  • 在不牺牲分类准确性的情况下,BTTOSCA实现了更小的特征子集.

结论:

  • 为了持续优化,TTOSCA为SCA提供了强大的增强功能.
  • BTTOSCA是一个强大而高效的工具,用于在高维和离散领域的特征选择.