情報処理学会研究報告 IPSJ SIG Technical Report Vol.2015-SE-187 No /3/13 Simulink 1,a) 1,b) 2 3 MATLAB/Simulink Simulink MATLAB/Simulink A Study of Qualit
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1 Simulink 1,a) 1,b) 2 3 MATLAB/Simulink Simulink MATLAB/Simulink A Study of Quality Evaluation Method Using Division Determination by Simulink Model Metrics Minegishi Kengo 1,a) Ueda Yoshikazu 1,b) Hukazu Takashi 2 Kubo Takayuki 3 Abstract: Currently, the model-based development using MATLAB/Simulink at development site of many embedded systems have been made. In recent years, according as the embedded systems become highperformance, System development with Simulink are seeking high quality and efficiency in model design. In previous research, because analytical accuracy is low, these techniques do not give satisfactory evaluation results. In this study, I classified the data flow layer and the structure layer for purpose of accuracy improvement. I considered the model evaluation method using the discrimination result of Simulink model layer type. Keywords: MATLAB/Simulink, Model metrics, Multivariate analysis, Multiple regression analysis, Discriminant analysis 1. MATLAB/Simulink Simulink 1 Presently with Ibaraki Uniersity 2 Presently with AISIN COMCRUISE Co.,Ltd. 3 Presently with AISIN AW Co.,Ltd. a) 13nm719t@hcs.ibaraki.ac.jp b) ueda@mx.ibaraki.ac.jp Simulink UML (metrics:) Simulink *1 Simulink *1 Simulink exmotion exquto for MBD c 2015 Information Processing Society of Japan 1
2 Simulink 4 Simulink Simulink 2 Simulnk MATLAB/Simulink MATLAB [1] Simulink MATLAB MATLAB 1 [2] Simulink 2.2 (Line Of Code) (Cyclomatic complexity) 2.3 Leave-one-out (LOOVC) Leave-oneout 1 (F ) t c 2015 Information Processing Society of Japan 2
3 80% 2.4 Simulink MathWorks Simulink [4][5] UML [6] UML Simulink 1 Simulink Simulink JMAAB [9] MATLAB/Simulink Simulink 3.3 Simulnk UML [7] Simulink Simulink 1 1 Table 1 Definition of Metrics VIF c 2015 Information Processing Society of Japan 3
4 Fig. 1 1 Flow of the Quality Evaluation Method 2 Leave-one-out (LOOCV) Simulink (F ) Simulink 14 Simulink Simulink Z JMAAB Simulink [9] Table 2 The number of sub-systems belong to each group F c 2015 Information Processing Society of Japan 4
5 3 Table 3 Comparison of layer discriminant model (Data flow layer) Table 4 Comparison of layer discriminant model (Structure layer) Table 5 Decision result of each discriminant model for estimating the model layer Simulink 82 good bad 50 5 good bad 7 8 good bad Z 1,2 Simulink 78 2 Simulink 78 good bad % 80% 1 3 2% 2% 1 5 F 2.0 F 6 6 2% 2 3 X Y c 2015 Information Processing Society of Japan 5
6 6 Table 6 estimated results of the regression model for estimating the quality 2% 80% E E E E+05 F E E E E+34 F E E E E+05 (1 ) F n Table 7 7 Number of calculations of regression model 2 ( 2% ) Fig. 2 Scatter plot of the evaluation score and the predicted score (contribution rate by 2% or more) ( 21 ) ( n ) n n k=1 k = 2.1E n 3 ( ) Fig. 3 Scatter plot of the evaluation score and the predicted score (forward selection method) [7][8] c 2015 Information Processing Society of Japan 6
7 Simulink. [1] The MathWorks:MATLAB [2] The MathWorks:Simulink, [3] :, seminar/result.htm. [4] The MathWorks:MathWorks Automotive Advisory Board (MAAB) [5] JMAAB Japan MATLAB Automotive Advisory Board) [6],, :UML,,,Vol.49,No.7,pp (2009) [7],, :Simulink,, vol.112, no.496, KBSE , pp.7-12(2013) [8],,,, : Simulink, c 2015 Information Processing Society of Japan 7
8 2014 (2014) [9] CONTROL ALGORITHM MODELING GUIDELINES USING MATLAB R, Simulink R and Stateflow R Version 2.0 c 2015 Information Processing Society of Japan 8
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