Modeling and prediction using an artificial neural network to study the impact of foreign direct investment on the growth rate / a case study of the State of Qatar

Al-Thalabi, Sahera Hussein Zain; Heydari, Ali Akbar; Tavakoli, Masoud

doi:10.1080/09720510.2022.2060914

Cited by 1 publication

(1 citation statement)

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“…MLP is a traditional, fully connected neural network that consists of an input layer, hidden layers, and output layer, in which the number of hidden layers can be set according to research needs. MLP currently plays an important role in dealing with regression and classification problems, and it has been successfully applied to image processing [ 37 ], semantic processing [ 38 ], and financial analysis [ 39 ]. The schematic diagram of MLP used in this manuscript to process OFDR data is shown in Figure 2 .…”

Section: Theorymentioning

confidence: 99%

Optical Frequency Domain Reflectometry Based on Multilayer Perceptron

Yin

Zhu

Liu

et al. 2023

Sensors

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We proposed an optical frequency domain reflectometry based on a multilayer perceptron. A classification multilayer perceptron was applied to train and grasp the fingerprint features of Rayleigh scattering spectrum in the optical fiber. The training set was constructed by moving the reference spectrum and adding the supplementary spectrum. Strain measurement was employed to verify the feasibility of the method. Compared with the traditional cross-correlation algorithm, the multilayer perceptron achieves a larger measurement range, better measurement accuracy, and is less time-consuming. To our knowledge, this is the first time that machine learning has been introduced into an optical frequency domain reflectometry system. Such thoughts and results would bring new knowledge and optimization to the optical frequency domain reflectometer system.

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Section: Theorymentioning

confidence: 99%