Quantitative Inversion Modeling Method for Grading Deerni Copper Deposits Based on Visible and Near-Infrared Hyperspectral Data

Wang, Jingli; Gao, Jingxiang; Huang, Jiaqi; Qi, Qing-Hui; Mao, Xinqi; Cao, Wang; Ding, Ruibo; Mao, Yachun

doi:10.1080/07038992.2022.2059755

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…Taking Morden as an example, they believe that the positioning of small towns needs to consider a variety of factors, such as regional advantages, mature characteristic industries and cultural and creative industries, and local policy guidance. e authors (Vukovi ć Predrag, Č Avlin Gordana, and Č Avlin Miroslav) in various works proposed that the success of both rural tourism town in the UK benefits from natural hot spring resources, location conditions, and convenient transportation [16][17][18][19]. When studying the STP theory, (Daan Francois Toerien) found that the cultural and tourism towns have achieved good benefits in the innovative use of local characteristic resources [23,24].…”

Section: Related Workmentioning

confidence: 99%

Location Selection of Digital Cultural Tourism Town Based on Improved Genetic Algorithm and BP Neural Network

LeahWu

Qiao

Jia

et al. 2022

Mobile Information Systems

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Due to the short development time of cultural and tourism towns in China, local governments and investors lack experience in building cultural and tourism towns and do not pay enough attention to the positioning of towns. Alternatively, this issue results in chaos in domestic cultural and tourism towns and even a large number of empty towns in some provinces. Therefore, how to accurately locate cultural tourism towns is a problem that must be studied in depth at present. This paper uses the regional economic theory to collect the influencing factors of cultural tourism town positioning. Based on the BP neural network and the improved genetic algorithm, a genetic neural network model is constructed to train and predict the samples of cultural tourism towns. Taking a small town in the East as a case, the data were collected and analyzed. Established on the prediction outcomes of the genetic neural network, the best location of a small town was selected according to the actual situation of the region. In terms of accuracy and training time, our experimental evaluation confirmed that the neural network enhanced by genetic algorithms outperforms the conventional BP neural network. Furthermore, we observed that besides the classification capabilities of the BP neural network-based model, the classical BP neural network improved by the genetic algorithm also exhibits great macrosearch capabilities and good global optimization performance.

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Section: Related Workmentioning

confidence: 99%

Location Selection of Digital Cultural Tourism Town Based on Improved Genetic Algorithm and BP Neural Network

LeahWu

Qiao

Jia

et al. 2022

Mobile Information Systems

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“…Manna et al 13 developed a multilayer feedforward neural network model to estimate copper grade in copper ore, establishing a functional relationship between hyperspectral reectance features and copper grade. Wang et al 14 devised a quantitative inversion model for copper grade using hyperspectral data, enabling real-time in situ determination of ore body grades. The above HSI technique had been utilized to assess the quality of minerals by evaluating single ore components (e.g., Fe or Cu grade), and its application in multicomponent systems was not yet clear.…”

Section: Introductionmentioning

confidence: 99%

Multicomponent hyperspectral grade evaluation of ilmenite using spectral-spatial joint features

Yi,

Chen,

Guo

et al. 2023

Anal. Methods

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Feature construction methods for processing and analysing spectral images and their applications in food quality inspection

Sun

et al. 2023

Trends in Food Science & Technology

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Quantitative Inversion Modeling Method for Grading Deerni Copper Deposits Based on Visible and Near-Infrared Hyperspectral Data

Cited by 5 publications

References 44 publications

Location Selection of Digital Cultural Tourism Town Based on Improved Genetic Algorithm and BP Neural Network

Location Selection of Digital Cultural Tourism Town Based on Improved Genetic Algorithm and BP Neural Network

Multicomponent hyperspectral grade evaluation of ilmenite using spectral-spatial joint features

Feature construction methods for processing and analysing spectral images and their applications in food quality inspection

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