Analysis of the Samples with an Unknown Matrix Using Data Mining Algorithms

Molchanova, E. I.; Korzhova, E. N.; Степанова, Т. В.; Kuz’min, V. V.

doi:10.1134/s0020168517140138

Cited by 4 publications

(1 citation statement)

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“…In terms of the current popular pretraining language model, Yu used hundreds of millions of words of biomedical text mixed general language text to train the biomedical corpus [13]. Molchanova and others used 1.14 million biomedical and computer science and technology documents for the training of sciences, which is best suited to the management of scientific and technological documents in China; some researchers have formed the Chinese pretraining model of SciBERT CN using the corpus of Chinese scientific and technological documents [14]. Hasheminejad and Khorrami found that, at present, the researchers tried to produce documents using the pretraining model.…”

Section: Literature Reviewmentioning

confidence: 99%

Practical Skills of Business English Correspondence Writing Based on Data Mining Algorithm

Liu

Habil

2022

Scientific Programming

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English correspondence writing has become a necessary skill for every scientific researcher and high-tech talents. An English correspondence writing auxiliary writing system can help nonnative English speakers make up for the lack of professional expression. The key factor of business English correspondence writing system is the construction of knowledge base. To improve the business English correspondence writing knowledge base, we need to mine frequent patterns of sentences in each category. The purpose of this topic is to improve and supplement the knowledge base for the business English correspondence writing system and propose frequent pattern mining for sentences in each category, so as to improve the writing knowledge base for the business English correspondence writing system. Firstly, we crawl a large number of business English letters and telegrams from the Internet, extract the relevant summary information, then store it, and preliminarily construct a corpus based on sentences. Then, we do some research on the structure of business English correspondence abstracts, mark the sentences in the corpus and count the relevant information, and have a certain understanding of their writing methods. Finally, we mine frequent patterns for sentences in each category, so as to improve the knowledge base of summary writing for the business English correspondence writing system. In the experiment, we use the classical FP growth algorithm as the mining method. The experiment shows that the frequent patterns between 3 and 6 words have been mined to a certain extent. By gradually improving the mining strategy, the quality of mining results has been improved and the writing effect of business English correspondence of scientific researchers has been improved.

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Section: Literature Reviewmentioning

confidence: 99%

Practical Skills of Business English Correspondence Writing Based on Data Mining Algorithm

Liu

Habil

2022

Scientific Programming

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Clustering and Evolutionary System Analysis of Data Mining Algorithms in the Field of Football

Wang¹

2022

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)

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Assessment of the possibility of modeling nonlinear multivariable calibration function using artificial neural networks

Molchanova

Korzhova

Федоров

et al. 2021

Zavod. lab., Diagn. mater.

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The use of artificial neural networks (ANNs) is considered justified when studying the problems that do not have a generally accepted solution algorithm. One of such problems in X-ray fluorescence analysis (XRF) is a control of the metal content in atmospheric air and air of the working area. Determination of the calibration characteristics is raveled by the lack of standard samples of the composition of aerosols collected on the filter. To solve this problem, synthetic calibration samples (CS) were manufactured as a thin organic film containing a powder material of the known chemical composition. The weight of the film samples varied within a range of 40 – 155 mg to simulate different aerosol loading of the filters and the content of components in them changed 20 – 200 times which corresponds to the samples of real aerosols. The possibility of modeling a nonlinear calibration multivariable function using artificial neural networks was evaluated in analysis of 38 film calibration samples (from 40 to 100 mg). The structure of the neural network, activation functions, learning algorithms have been investigated. Modeling was performed using an academic version of the BaseGroup Deductor analytical platform. It is shown that implementation of the back propagation of errors leads to much higher values of the error of analysis compared to the error of the regression calibration functions, whereas the Resilient Propagation algorithm provides the smallest values of the error of vanadium determination (Sr) in the calibration samples of aerosols. The range of low content of the elements in the training set is determined with a greater error compared to high content range, and therefore, the sigmoid activation function leads to unsatisfactory accuracy of the analysis results, and preference should be given to hyperbolic tangent (tanh).

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Analysis of the Samples with an Unknown Matrix Using Data Mining Algorithms

Cited by 4 publications

References 0 publications

Practical Skills of Business English Correspondence Writing Based on Data Mining Algorithm

Practical Skills of Business English Correspondence Writing Based on Data Mining Algorithm

Clustering and Evolutionary System Analysis of Data Mining Algorithms in the Field of Football

Assessment of the possibility of modeling nonlinear multivariable calibration function using artificial neural networks

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