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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 4
1143-1147

Grain flour classification and hardware acceleration based on random forest algorithm

Xu Leijun
Xiang Houyou
Ni Lihua
School of Electrical Information Engineering, Jiangsu University, Zhengjiang Jiangsu 212013, China
DOI: 10.19734/j.issn.1001-3695.2021.09.0418

Abstract

In view of the slow detection speed of traditional grain flour species, this study implemented the random forest algorithm-assisted microwave nondestructive testing technology to identify grain flour species efficiently and accurately based on ZYNQ platform. By analyzing the hardware implementation of the random forest model, this paper proposed an improved model parameter structure, which could effectively save the consumption of hardware storage resources. In order to shorten the prediction time of the algorithm and reduce the power consumption of the system, it introduced the early termination recognition mechanism in the hardware implementation to avoid the unnecessary decision tree prediction process on the premise of keeping the accuracy unchanged. In view of the Zedboard development board, it designed a storage scheme for model parameters to make full use of on-board resources and ensure the normal operation of the system. The experimental results show that the implementation time of the scheme with ZYNQ is about 54.2% shorter than that of the random forest algorithm with traditional CPU, and no loss of recognition accuracy is caused.

Foundation Support

国家自然科学基金资助项目(61874050)
江苏省自然科学基金资助项目(SJCX20_1403)
江苏省农业科技自主创新项目(CX(17)3001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.09.0418
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 4
Section: System Development & Application
Pages: 1143-1147
Serial Number: 1001-3695(2022)04-031-1143-05

Publish History

[2021-12-07] Accepted Paper
[2022-04-05] Printed Article

Cite This Article

徐雷钧, 项厚友, 倪利华. 基于随机森林算法的谷物粉分类及硬件加速 [J]. 计算机应用研究, 2022, 39 (4): 1143-1147. (Xu Leijun, Xiang Houyou, Ni Lihua. Grain flour classification and hardware acceleration based on random forest algorithm [J]. Application Research of Computers, 2022, 39 (4): 1143-1147. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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