Research on the Method of Material Scheme Matching Based on Deep Learning
DOI: 10.23977/cpcs.2021.51005 | Downloads: 10 | Views: 1270
Author(s)
Weidong Kang 1, Hao Gu 1, Qi Ruan 1, Neng Zhao 1
Affiliation(s)
1 Anhui Nanrui Jiyuan Power Grid Technology Co., Ltd., Hefei, Anhui Province, China
Corresponding Author
Hao GuABSTRACT
Based on the research of the deep learning network and the material scheme matching method, a material scheme matching method based on the combination of materials, solid ID data and multi-layer perceptrons is proposed. Based on the relationship among engineering design standards, general equipment selection and material procurement standards, a material and solidified ID data information system is formed. Then, collect, sort, and model electrical primary and secondary equipment and line information to form a model structure of plans and materials; finally, integrate and analyze historical data to form a typical plan material matching library. The training of the perceptron network obtains the material plan matching network. Experimental results show that the matching method of material schemes using materials, solidified ID data and multilayer perceptron network can achieve 96% matching accuracy, which solves the problem of information barriers in design standards, general equipment requirements and material procurement standards. The development of the material plan provides new ideas.
KEYWORDS
Material plan matching, Multilayer perceptron, Engineering design standards, Solidify id dataCITE THIS PAPER
Jun Liu, Kejun Yang, Daping Liu, Hui He, Tao Cheng, He Xu, Wenzhi Han, Research on the Method of Material Scheme Matching Based on Deep Learning. Computing, Performance and Communication Systems (2021) Vol. 5: 24-29. DOI: http://dx.doi.org/10.23977/cpcs.2021.51005
REFERENCES
[1] Yin X Y , Zong Z Y , Wu G C . Research on seismic fluid identification driven by rock physics[J]. Science China Earth Sciences, 2015.
[2] Carli L D , Sommer R , Jha S . Beyond Pattern Matching: A Concurrency Model for Stateful Deep Packet Inspection[C]// Acm Conference on Computer & Communications Security. ACM, 2014.
[3] Ke Cao, Chang Wu. Analysis and Study of Influence Factors and Control Strategies For Power Grid Operation Costs[J]. Global journal of Economics and Business Administration,2019,3(16).
[4] Mobahi H , Iii J W F . On the Link between Gaussian Homotopy Continuation and Convex Envelopes[J]. 2015.
[5] Jing Nie. Smart Grid Construction Based on Perspective of the Development of Servicing Clean Energy[J]. Advanced Materials Research,2013,2568..
[6] Lee S , Hong H , Eem C . Voxel-Based Scene Representation for Camera Pose Estimation of a Single RGB Image[J]. Applied Sciences, 2020, 10(24):8866.
[7] Wang X , Zhang X , Shahzad M M . A novel structural damage identification scheme based on deep learning framework[J]. Structures, 2021, 29:1537-1549.
[8] Choi D J , Lee H B , Wee J W , et al. k-Nearest Neighbor Query Optimization Scheme Based on Deep Learning in a Distributed High Dimensional Index[J]. ICCC, 2019.
[9] Pop D O , Rogozan A , Nashashibi F , et al. Pedestrian Recognition through Different Cross-Modality Deep Learning Methods[C]// IEEE International Conference on Vehicular Electronics & Safety. IEEE, 2017.
[10] Mi Z . Method of growing uniform semiconductor nanowires without foreign metal catalyst and devices thereof[J]. 2013.
[11] Page V T N . Van Tâm NGUYEN : Research[J].
[12] Armato S G , Petrick N A , Nppi J J , et al. Deep learning of contrast-coated serrated polyps for computer-aided detection in CT colonography[C]// SPIE Medical Imaging. Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, 2017.
[13] YANG KJ, XIONG MM. Prediction of CH4 adsorption on different activated carbons by developing an optimal multilayer perceptron artificial neural network [J]. Energy Sources Part A-recovery Utilization And Environmental Effects. 2018, 41(17): 2061-2072.
[14] Rynkiewicz J. Asymptotic statistics for multilayer perceptron with ReLU hidden units [J]. Neurocomputing. 2018, (342): 16-23.
[15] Castro W, Oblitas J, Santa-Cruz R, et al. Multilayer perceptron architecture optimization using parallel computing techniques[J]. PLOS ONE, 2017, 12(12) : e0189369.
[16] Castro W, Oblitas J, Santa-Cruz R, et al. Multilayer perceptron architecture optimization using parallel computing techniques[J]. PLOS ONE, 2017, 12(12) : e0189369.
[17] Engel, E. А, Kovalev I V . Information processing using intelligent algorithms by solving wcci 2010 tasks[J]. 2011.
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