Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models

In this paper, a novel concept of optimal space-filling identifiable design is proposed in the framework of symmetrical global sensitivity analysis for exploring complex black-box models. The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Wang, Xiaodi [verfasserIn] Tsung, Fugee [verfasserIn] Li, Wendong [verfasserIn] Xiang, Dongdong [verfasserIn] Cheng, Chao [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Complex black-box model Identifiable design Space filling Symmetrical global sensitivity analysis Track substitution

Übergeordnetes Werk:	Enthalten in: Applied mathematical modelling - Amsterdam [u.a.] : Elsevier Science, 1976, 100, Seite 303-319
Übergeordnetes Werk:	volume:100 ; pages:303-319

DOI / URN:	10.1016/j.apm.2021.08.015

Katalog-ID:	ELV006626726

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520			\|a In this paper, a novel concept of optimal space-filling identifiable design is proposed in the framework of symmetrical global sensitivity analysis for exploring complex black-box models. The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of space filling, the ϕ q and L 2 -discrepancy criterions, two optimal space-filling identifiable designs are proposed. The corresponding optimization algorithms are also given, in which adjacent identifiable designs are produced sequentially by using track substitution until the space-filling property has been optimized. By using the resulting optimal space-filling identifiable design, symmetrical global sensitivity indices can be directly estimated based on model outputs with high precision. Extensive theoretical and numerical results demonstrate the optimality and effectiveness of the proposed designs, as well as the superiority over the existing designs in the literature. Technical details are provided in the Appendix.
650		4	\|a Complex black-box model
650		4	\|a Identifiable design
650		4	\|a Space filling
650		4	\|a Symmetrical global sensitivity analysis
650		4	\|a Track substitution
700	1		\|a Tsung, Fugee \|e verfasserin \|4 aut
700	1		\|a Li, Wendong \|e verfasserin \|4 aut
700	1		\|a Xiang, Dongdong \|e verfasserin \|4 aut
700	1		\|a Cheng, Chao \|e verfasserin \|4 aut
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author_variant	x w xw f t ft w l wl d x dx c c cc
matchkey_str	wangxiaoditsungfugeeliwendongxiangdongdo:2021----:piasaeilndsgfrymtiagoasniiiynls
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allfields	10.1016/j.apm.2021.08.015 doi (DE-627)ELV006626726 (ELSEVIER)S0307-904X(21)00379-6 DE-627 ger DE-627 rda eng 510 DE-600 31.80 bkl 50.03 bkl Wang, Xiaodi verfasserin aut Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel concept of optimal space-filling identifiable design is proposed in the framework of symmetrical global sensitivity analysis for exploring complex black-box models. The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of space filling, the ϕ q and L 2 -discrepancy criterions, two optimal space-filling identifiable designs are proposed. The corresponding optimization algorithms are also given, in which adjacent identifiable designs are produced sequentially by using track substitution until the space-filling property has been optimized. By using the resulting optimal space-filling identifiable design, symmetrical global sensitivity indices can be directly estimated based on model outputs with high precision. Extensive theoretical and numerical results demonstrate the optimality and effectiveness of the proposed designs, as well as the superiority over the existing designs in the literature. Technical details are provided in the Appendix. Complex black-box model Identifiable design Space filling Symmetrical global sensitivity analysis Track substitution Tsung, Fugee verfasserin aut Li, Wendong verfasserin aut Xiang, Dongdong verfasserin aut Cheng, Chao verfasserin aut Enthalten in Applied mathematical modelling Amsterdam [u.a.] : Elsevier Science, 1976 100, Seite 303-319 Online-Ressource (DE-627)32043432X (DE-600)2004151-2 (DE-576)256143366 nnns volume:100 pages:303-319 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 31.80 Angewandte Mathematik 50.03 Methoden und Techniken der Ingenieurwissenschaften AR 100 303-319
spelling	10.1016/j.apm.2021.08.015 doi (DE-627)ELV006626726 (ELSEVIER)S0307-904X(21)00379-6 DE-627 ger DE-627 rda eng 510 DE-600 31.80 bkl 50.03 bkl Wang, Xiaodi verfasserin aut Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel concept of optimal space-filling identifiable design is proposed in the framework of symmetrical global sensitivity analysis for exploring complex black-box models. The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of space filling, the ϕ q and L 2 -discrepancy criterions, two optimal space-filling identifiable designs are proposed. The corresponding optimization algorithms are also given, in which adjacent identifiable designs are produced sequentially by using track substitution until the space-filling property has been optimized. By using the resulting optimal space-filling identifiable design, symmetrical global sensitivity indices can be directly estimated based on model outputs with high precision. Extensive theoretical and numerical results demonstrate the optimality and effectiveness of the proposed designs, as well as the superiority over the existing designs in the literature. Technical details are provided in the Appendix. Complex black-box model Identifiable design Space filling Symmetrical global sensitivity analysis Track substitution Tsung, Fugee verfasserin aut Li, Wendong verfasserin aut Xiang, Dongdong verfasserin aut Cheng, Chao verfasserin aut Enthalten in Applied mathematical modelling Amsterdam [u.a.] : Elsevier Science, 1976 100, Seite 303-319 Online-Ressource (DE-627)32043432X (DE-600)2004151-2 (DE-576)256143366 nnns volume:100 pages:303-319 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 31.80 Angewandte Mathematik 50.03 Methoden und Techniken der Ingenieurwissenschaften AR 100 303-319
allfields_unstemmed	10.1016/j.apm.2021.08.015 doi (DE-627)ELV006626726 (ELSEVIER)S0307-904X(21)00379-6 DE-627 ger DE-627 rda eng 510 DE-600 31.80 bkl 50.03 bkl Wang, Xiaodi verfasserin aut Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel concept of optimal space-filling identifiable design is proposed in the framework of symmetrical global sensitivity analysis for exploring complex black-box models. The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of space filling, the ϕ q and L 2 -discrepancy criterions, two optimal space-filling identifiable designs are proposed. The corresponding optimization algorithms are also given, in which adjacent identifiable designs are produced sequentially by using track substitution until the space-filling property has been optimized. By using the resulting optimal space-filling identifiable design, symmetrical global sensitivity indices can be directly estimated based on model outputs with high precision. Extensive theoretical and numerical results demonstrate the optimality and effectiveness of the proposed designs, as well as the superiority over the existing designs in the literature. Technical details are provided in the Appendix. Complex black-box model Identifiable design Space filling Symmetrical global sensitivity analysis Track substitution Tsung, Fugee verfasserin aut Li, Wendong verfasserin aut Xiang, Dongdong verfasserin aut Cheng, Chao verfasserin aut Enthalten in Applied mathematical modelling Amsterdam [u.a.] : Elsevier Science, 1976 100, Seite 303-319 Online-Ressource (DE-627)32043432X (DE-600)2004151-2 (DE-576)256143366 nnns volume:100 pages:303-319 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 31.80 Angewandte Mathematik 50.03 Methoden und Techniken der Ingenieurwissenschaften AR 100 303-319
allfieldsGer	10.1016/j.apm.2021.08.015 doi (DE-627)ELV006626726 (ELSEVIER)S0307-904X(21)00379-6 DE-627 ger DE-627 rda eng 510 DE-600 31.80 bkl 50.03 bkl Wang, Xiaodi verfasserin aut Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel concept of optimal space-filling identifiable design is proposed in the framework of symmetrical global sensitivity analysis for exploring complex black-box models. The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of space filling, the ϕ q and L 2 -discrepancy criterions, two optimal space-filling identifiable designs are proposed. The corresponding optimization algorithms are also given, in which adjacent identifiable designs are produced sequentially by using track substitution until the space-filling property has been optimized. By using the resulting optimal space-filling identifiable design, symmetrical global sensitivity indices can be directly estimated based on model outputs with high precision. Extensive theoretical and numerical results demonstrate the optimality and effectiveness of the proposed designs, as well as the superiority over the existing designs in the literature. Technical details are provided in the Appendix. Complex black-box model Identifiable design Space filling Symmetrical global sensitivity analysis Track substitution Tsung, Fugee verfasserin aut Li, Wendong verfasserin aut Xiang, Dongdong verfasserin aut Cheng, Chao verfasserin aut Enthalten in Applied mathematical modelling Amsterdam [u.a.] : Elsevier Science, 1976 100, Seite 303-319 Online-Ressource (DE-627)32043432X (DE-600)2004151-2 (DE-576)256143366 nnns volume:100 pages:303-319 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 31.80 Angewandte Mathematik 50.03 Methoden und Techniken der Ingenieurwissenschaften AR 100 303-319
allfieldsSound	10.1016/j.apm.2021.08.015 doi (DE-627)ELV006626726 (ELSEVIER)S0307-904X(21)00379-6 DE-627 ger DE-627 rda eng 510 DE-600 31.80 bkl 50.03 bkl Wang, Xiaodi verfasserin aut Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel concept of optimal space-filling identifiable design is proposed in the framework of symmetrical global sensitivity analysis for exploring complex black-box models. The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of space filling, the ϕ q and L 2 -discrepancy criterions, two optimal space-filling identifiable designs are proposed. The corresponding optimization algorithms are also given, in which adjacent identifiable designs are produced sequentially by using track substitution until the space-filling property has been optimized. By using the resulting optimal space-filling identifiable design, symmetrical global sensitivity indices can be directly estimated based on model outputs with high precision. Extensive theoretical and numerical results demonstrate the optimality and effectiveness of the proposed designs, as well as the superiority over the existing designs in the literature. Technical details are provided in the Appendix. Complex black-box model Identifiable design Space filling Symmetrical global sensitivity analysis Track substitution Tsung, Fugee verfasserin aut Li, Wendong verfasserin aut Xiang, Dongdong verfasserin aut Cheng, Chao verfasserin aut Enthalten in Applied mathematical modelling Amsterdam [u.a.] : Elsevier Science, 1976 100, Seite 303-319 Online-Ressource (DE-627)32043432X (DE-600)2004151-2 (DE-576)256143366 nnns volume:100 pages:303-319 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 31.80 Angewandte Mathematik 50.03 Methoden und Techniken der Ingenieurwissenschaften AR 100 303-319
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author	Wang, Xiaodi
spellingShingle	Wang, Xiaodi ddc 510 bkl 31.80 bkl 50.03 misc Complex black-box model misc Identifiable design misc Space filling misc Symmetrical global sensitivity analysis misc Track substitution Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models
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topic_title	510 DE-600 31.80 bkl 50.03 bkl Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models Complex black-box model Identifiable design Space filling Symmetrical global sensitivity analysis Track substitution
topic	ddc 510 bkl 31.80 bkl 50.03 misc Complex black-box model misc Identifiable design misc Space filling misc Symmetrical global sensitivity analysis misc Track substitution
topic_unstemmed	ddc 510 bkl 31.80 bkl 50.03 misc Complex black-box model misc Identifiable design misc Space filling misc Symmetrical global sensitivity analysis misc Track substitution
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title	Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models
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title_full	Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models
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title_sort	optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models
title_auth	Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models
abstract	In this paper, a novel concept of optimal space-filling identifiable design is proposed in the framework of symmetrical global sensitivity analysis for exploring complex black-box models. The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of space filling, the ϕ q and L 2 -discrepancy criterions, two optimal space-filling identifiable designs are proposed. The corresponding optimization algorithms are also given, in which adjacent identifiable designs are produced sequentially by using track substitution until the space-filling property has been optimized. By using the resulting optimal space-filling identifiable design, symmetrical global sensitivity indices can be directly estimated based on model outputs with high precision. Extensive theoretical and numerical results demonstrate the optimality and effectiveness of the proposed designs, as well as the superiority over the existing designs in the literature. Technical details are provided in the Appendix.
abstractGer	In this paper, a novel concept of optimal space-filling identifiable design is proposed in the framework of symmetrical global sensitivity analysis for exploring complex black-box models. The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of space filling, the ϕ q and L 2 -discrepancy criterions, two optimal space-filling identifiable designs are proposed. The corresponding optimization algorithms are also given, in which adjacent identifiable designs are produced sequentially by using track substitution until the space-filling property has been optimized. By using the resulting optimal space-filling identifiable design, symmetrical global sensitivity indices can be directly estimated based on model outputs with high precision. Extensive theoretical and numerical results demonstrate the optimality and effectiveness of the proposed designs, as well as the superiority over the existing designs in the literature. Technical details are provided in the Appendix.
abstract_unstemmed	In this paper, a novel concept of optimal space-filling identifiable design is proposed in the framework of symmetrical global sensitivity analysis for exploring complex black-box models. The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of space filling, the ϕ q and L 2 -discrepancy criterions, two optimal space-filling identifiable designs are proposed. The corresponding optimization algorithms are also given, in which adjacent identifiable designs are produced sequentially by using track substitution until the space-filling property has been optimized. By using the resulting optimal space-filling identifiable design, symmetrical global sensitivity indices can be directly estimated based on model outputs with high precision. Extensive theoretical and numerical results demonstrate the optimality and effectiveness of the proposed designs, as well as the superiority over the existing designs in the literature. Technical details are provided in the Appendix.
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title_short	Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models
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author2	Tsung, Fugee Li, Wendong Xiang, Dongdong Cheng, Chao
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up_date	2024-07-06T22:01:08.990Z
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The initial identifiable design is first generated algorithmically. Then based on two commonly used measures of space filling, the ϕ q and L 2 -discrepancy criterions, two optimal space-filling identifiable designs are proposed. The corresponding optimization algorithms are also given, in which adjacent identifiable designs are produced sequentially by using track substitution until the space-filling property has been optimized. By using the resulting optimal space-filling identifiable design, symmetrical global sensitivity indices can be directly estimated based on model outputs with high precision. Extensive theoretical and numerical results demonstrate the optimality and effectiveness of the proposed designs, as well as the superiority over the existing designs in the literature. 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Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models

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