A Multiple and Multidimensional Linguistic Truth-Valued Reasoning Method and its Application in Multimedia Teaching Evaluation
Abstract With the expansion of the epidemic, online multimedia teaching has become a common trend. The reasoning model of multimedia teaching evaluation is a useful tool to infer the result of teaching effects and predict the tendency. However, the ambiguity in the linguistic-valued evaluation leads...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Lu, Yifan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
Linguistic truth-valued intuitionistic fuzzy reasoning |
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| Anmerkung: |
© The Author(s) 2022 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of computational intelligence systems - Paris : Atlantis Press, 2008, 15(2022), 1 vom: 27. Mai |
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| Übergeordnetes Werk: |
volume:15 ; year:2022 ; number:1 ; day:27 ; month:05 |
| Links: |
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| DOI / URN: |
10.1007/s44196-022-00085-6 |
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SPR047116730 |
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| 520 | |a Abstract With the expansion of the epidemic, online multimedia teaching has become a common trend. The reasoning model of multimedia teaching evaluation is a useful tool to infer the result of teaching effects and predict the tendency. However, the ambiguity in the linguistic-valued evaluation leads to reasoning problems always in the context with uncertainty. To make the reasoning model better deal with multiple and multidimensional reasoning problems in uncertainty environment, while considering both positive evidence and negative evidence at the same time, this paper mainly focuses on a linguistic truth-valued intuitionistic fuzzy layered aggregation (LTV-IFLA) reasoning method. First, based on the layered linguistic truth-valued intuitionistic fuzzy lattice (LTV-IFL), we realize aggregating the linguistic truth-valued information through the layered average aggregation (LAA) operator presented by this paper. Furthermore, a layered weighted average aggregation (LWAA) operator is proposed to consider setting different weights to achieve personalization of the reasoning results. Finally, a multiple multidimensional reasoning model which simulates the reasoning of human language is presented to illustrate the method’s rationality and validity. | ||
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10.1007/s44196-022-00085-6 doi (DE-627)SPR047116730 (SPR)s44196-022-00085-6-e DE-627 ger DE-627 rakwb eng Lu, Yifan verfasserin aut A Multiple and Multidimensional Linguistic Truth-Valued Reasoning Method and its Application in Multimedia Teaching Evaluation 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract With the expansion of the epidemic, online multimedia teaching has become a common trend. The reasoning model of multimedia teaching evaluation is a useful tool to infer the result of teaching effects and predict the tendency. However, the ambiguity in the linguistic-valued evaluation leads to reasoning problems always in the context with uncertainty. To make the reasoning model better deal with multiple and multidimensional reasoning problems in uncertainty environment, while considering both positive evidence and negative evidence at the same time, this paper mainly focuses on a linguistic truth-valued intuitionistic fuzzy layered aggregation (LTV-IFLA) reasoning method. First, based on the layered linguistic truth-valued intuitionistic fuzzy lattice (LTV-IFL), we realize aggregating the linguistic truth-valued information through the layered average aggregation (LAA) operator presented by this paper. Furthermore, a layered weighted average aggregation (LWAA) operator is proposed to consider setting different weights to achieve personalization of the reasoning results. Finally, a multiple multidimensional reasoning model which simulates the reasoning of human language is presented to illustrate the method’s rationality and validity. Lattice implication algebra (dpeaa)DE-He213 Linguistic truth-valued intuitionistic fuzzy reasoning (dpeaa)DE-He213 Multiple multidimensional reasoning (dpeaa)DE-He213 Layered aggregation operator (dpeaa)DE-He213 Li, Nan aut Lin, Hongmei aut Zheng, Hongliang (orcid)0000-0002-6556-7433 aut Li, Xiaofeng aut Zou, Li aut Enthalten in International journal of computational intelligence systems Paris : Atlantis Press, 2008 15(2022), 1 vom: 27. Mai (DE-627)777781514 (DE-600)2754752-8 1875-6883 nnns volume:15 year:2022 number:1 day:27 month:05 https://dx.doi.org/10.1007/s44196-022-00085-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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 AR 15 2022 1 27 05 |
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10.1007/s44196-022-00085-6 doi (DE-627)SPR047116730 (SPR)s44196-022-00085-6-e DE-627 ger DE-627 rakwb eng Lu, Yifan verfasserin aut A Multiple and Multidimensional Linguistic Truth-Valued Reasoning Method and its Application in Multimedia Teaching Evaluation 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract With the expansion of the epidemic, online multimedia teaching has become a common trend. The reasoning model of multimedia teaching evaluation is a useful tool to infer the result of teaching effects and predict the tendency. However, the ambiguity in the linguistic-valued evaluation leads to reasoning problems always in the context with uncertainty. To make the reasoning model better deal with multiple and multidimensional reasoning problems in uncertainty environment, while considering both positive evidence and negative evidence at the same time, this paper mainly focuses on a linguistic truth-valued intuitionistic fuzzy layered aggregation (LTV-IFLA) reasoning method. First, based on the layered linguistic truth-valued intuitionistic fuzzy lattice (LTV-IFL), we realize aggregating the linguistic truth-valued information through the layered average aggregation (LAA) operator presented by this paper. Furthermore, a layered weighted average aggregation (LWAA) operator is proposed to consider setting different weights to achieve personalization of the reasoning results. Finally, a multiple multidimensional reasoning model which simulates the reasoning of human language is presented to illustrate the method’s rationality and validity. Lattice implication algebra (dpeaa)DE-He213 Linguistic truth-valued intuitionistic fuzzy reasoning (dpeaa)DE-He213 Multiple multidimensional reasoning (dpeaa)DE-He213 Layered aggregation operator (dpeaa)DE-He213 Li, Nan aut Lin, Hongmei aut Zheng, Hongliang (orcid)0000-0002-6556-7433 aut Li, Xiaofeng aut Zou, Li aut Enthalten in International journal of computational intelligence systems Paris : Atlantis Press, 2008 15(2022), 1 vom: 27. Mai (DE-627)777781514 (DE-600)2754752-8 1875-6883 nnns volume:15 year:2022 number:1 day:27 month:05 https://dx.doi.org/10.1007/s44196-022-00085-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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 AR 15 2022 1 27 05 |
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10.1007/s44196-022-00085-6 doi (DE-627)SPR047116730 (SPR)s44196-022-00085-6-e DE-627 ger DE-627 rakwb eng Lu, Yifan verfasserin aut A Multiple and Multidimensional Linguistic Truth-Valued Reasoning Method and its Application in Multimedia Teaching Evaluation 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract With the expansion of the epidemic, online multimedia teaching has become a common trend. The reasoning model of multimedia teaching evaluation is a useful tool to infer the result of teaching effects and predict the tendency. However, the ambiguity in the linguistic-valued evaluation leads to reasoning problems always in the context with uncertainty. To make the reasoning model better deal with multiple and multidimensional reasoning problems in uncertainty environment, while considering both positive evidence and negative evidence at the same time, this paper mainly focuses on a linguistic truth-valued intuitionistic fuzzy layered aggregation (LTV-IFLA) reasoning method. First, based on the layered linguistic truth-valued intuitionistic fuzzy lattice (LTV-IFL), we realize aggregating the linguistic truth-valued information through the layered average aggregation (LAA) operator presented by this paper. Furthermore, a layered weighted average aggregation (LWAA) operator is proposed to consider setting different weights to achieve personalization of the reasoning results. Finally, a multiple multidimensional reasoning model which simulates the reasoning of human language is presented to illustrate the method’s rationality and validity. Lattice implication algebra (dpeaa)DE-He213 Linguistic truth-valued intuitionistic fuzzy reasoning (dpeaa)DE-He213 Multiple multidimensional reasoning (dpeaa)DE-He213 Layered aggregation operator (dpeaa)DE-He213 Li, Nan aut Lin, Hongmei aut Zheng, Hongliang (orcid)0000-0002-6556-7433 aut Li, Xiaofeng aut Zou, Li aut Enthalten in International journal of computational intelligence systems Paris : Atlantis Press, 2008 15(2022), 1 vom: 27. Mai (DE-627)777781514 (DE-600)2754752-8 1875-6883 nnns volume:15 year:2022 number:1 day:27 month:05 https://dx.doi.org/10.1007/s44196-022-00085-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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 AR 15 2022 1 27 05 |
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10.1007/s44196-022-00085-6 doi (DE-627)SPR047116730 (SPR)s44196-022-00085-6-e DE-627 ger DE-627 rakwb eng Lu, Yifan verfasserin aut A Multiple and Multidimensional Linguistic Truth-Valued Reasoning Method and its Application in Multimedia Teaching Evaluation 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract With the expansion of the epidemic, online multimedia teaching has become a common trend. The reasoning model of multimedia teaching evaluation is a useful tool to infer the result of teaching effects and predict the tendency. However, the ambiguity in the linguistic-valued evaluation leads to reasoning problems always in the context with uncertainty. To make the reasoning model better deal with multiple and multidimensional reasoning problems in uncertainty environment, while considering both positive evidence and negative evidence at the same time, this paper mainly focuses on a linguistic truth-valued intuitionistic fuzzy layered aggregation (LTV-IFLA) reasoning method. First, based on the layered linguistic truth-valued intuitionistic fuzzy lattice (LTV-IFL), we realize aggregating the linguistic truth-valued information through the layered average aggregation (LAA) operator presented by this paper. Furthermore, a layered weighted average aggregation (LWAA) operator is proposed to consider setting different weights to achieve personalization of the reasoning results. Finally, a multiple multidimensional reasoning model which simulates the reasoning of human language is presented to illustrate the method’s rationality and validity. Lattice implication algebra (dpeaa)DE-He213 Linguistic truth-valued intuitionistic fuzzy reasoning (dpeaa)DE-He213 Multiple multidimensional reasoning (dpeaa)DE-He213 Layered aggregation operator (dpeaa)DE-He213 Li, Nan aut Lin, Hongmei aut Zheng, Hongliang (orcid)0000-0002-6556-7433 aut Li, Xiaofeng aut Zou, Li aut Enthalten in International journal of computational intelligence systems Paris : Atlantis Press, 2008 15(2022), 1 vom: 27. Mai (DE-627)777781514 (DE-600)2754752-8 1875-6883 nnns volume:15 year:2022 number:1 day:27 month:05 https://dx.doi.org/10.1007/s44196-022-00085-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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 AR 15 2022 1 27 05 |
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10.1007/s44196-022-00085-6 doi (DE-627)SPR047116730 (SPR)s44196-022-00085-6-e DE-627 ger DE-627 rakwb eng Lu, Yifan verfasserin aut A Multiple and Multidimensional Linguistic Truth-Valued Reasoning Method and its Application in Multimedia Teaching Evaluation 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract With the expansion of the epidemic, online multimedia teaching has become a common trend. The reasoning model of multimedia teaching evaluation is a useful tool to infer the result of teaching effects and predict the tendency. However, the ambiguity in the linguistic-valued evaluation leads to reasoning problems always in the context with uncertainty. To make the reasoning model better deal with multiple and multidimensional reasoning problems in uncertainty environment, while considering both positive evidence and negative evidence at the same time, this paper mainly focuses on a linguistic truth-valued intuitionistic fuzzy layered aggregation (LTV-IFLA) reasoning method. First, based on the layered linguistic truth-valued intuitionistic fuzzy lattice (LTV-IFL), we realize aggregating the linguistic truth-valued information through the layered average aggregation (LAA) operator presented by this paper. Furthermore, a layered weighted average aggregation (LWAA) operator is proposed to consider setting different weights to achieve personalization of the reasoning results. Finally, a multiple multidimensional reasoning model which simulates the reasoning of human language is presented to illustrate the method’s rationality and validity. Lattice implication algebra (dpeaa)DE-He213 Linguistic truth-valued intuitionistic fuzzy reasoning (dpeaa)DE-He213 Multiple multidimensional reasoning (dpeaa)DE-He213 Layered aggregation operator (dpeaa)DE-He213 Li, Nan aut Lin, Hongmei aut Zheng, Hongliang (orcid)0000-0002-6556-7433 aut Li, Xiaofeng aut Zou, Li aut Enthalten in International journal of computational intelligence systems Paris : Atlantis Press, 2008 15(2022), 1 vom: 27. Mai (DE-627)777781514 (DE-600)2754752-8 1875-6883 nnns volume:15 year:2022 number:1 day:27 month:05 https://dx.doi.org/10.1007/s44196-022-00085-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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 AR 15 2022 1 27 05 |
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A Multiple and Multidimensional Linguistic Truth-Valued Reasoning Method and its Application in Multimedia Teaching Evaluation |
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Abstract With the expansion of the epidemic, online multimedia teaching has become a common trend. The reasoning model of multimedia teaching evaluation is a useful tool to infer the result of teaching effects and predict the tendency. However, the ambiguity in the linguistic-valued evaluation leads to reasoning problems always in the context with uncertainty. To make the reasoning model better deal with multiple and multidimensional reasoning problems in uncertainty environment, while considering both positive evidence and negative evidence at the same time, this paper mainly focuses on a linguistic truth-valued intuitionistic fuzzy layered aggregation (LTV-IFLA) reasoning method. First, based on the layered linguistic truth-valued intuitionistic fuzzy lattice (LTV-IFL), we realize aggregating the linguistic truth-valued information through the layered average aggregation (LAA) operator presented by this paper. Furthermore, a layered weighted average aggregation (LWAA) operator is proposed to consider setting different weights to achieve personalization of the reasoning results. Finally, a multiple multidimensional reasoning model which simulates the reasoning of human language is presented to illustrate the method’s rationality and validity. © The Author(s) 2022 |
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Abstract With the expansion of the epidemic, online multimedia teaching has become a common trend. The reasoning model of multimedia teaching evaluation is a useful tool to infer the result of teaching effects and predict the tendency. However, the ambiguity in the linguistic-valued evaluation leads to reasoning problems always in the context with uncertainty. To make the reasoning model better deal with multiple and multidimensional reasoning problems in uncertainty environment, while considering both positive evidence and negative evidence at the same time, this paper mainly focuses on a linguistic truth-valued intuitionistic fuzzy layered aggregation (LTV-IFLA) reasoning method. First, based on the layered linguistic truth-valued intuitionistic fuzzy lattice (LTV-IFL), we realize aggregating the linguistic truth-valued information through the layered average aggregation (LAA) operator presented by this paper. Furthermore, a layered weighted average aggregation (LWAA) operator is proposed to consider setting different weights to achieve personalization of the reasoning results. Finally, a multiple multidimensional reasoning model which simulates the reasoning of human language is presented to illustrate the method’s rationality and validity. © The Author(s) 2022 |
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Abstract With the expansion of the epidemic, online multimedia teaching has become a common trend. The reasoning model of multimedia teaching evaluation is a useful tool to infer the result of teaching effects and predict the tendency. However, the ambiguity in the linguistic-valued evaluation leads to reasoning problems always in the context with uncertainty. To make the reasoning model better deal with multiple and multidimensional reasoning problems in uncertainty environment, while considering both positive evidence and negative evidence at the same time, this paper mainly focuses on a linguistic truth-valued intuitionistic fuzzy layered aggregation (LTV-IFLA) reasoning method. First, based on the layered linguistic truth-valued intuitionistic fuzzy lattice (LTV-IFL), we realize aggregating the linguistic truth-valued information through the layered average aggregation (LAA) operator presented by this paper. Furthermore, a layered weighted average aggregation (LWAA) operator is proposed to consider setting different weights to achieve personalization of the reasoning results. Finally, a multiple multidimensional reasoning model which simulates the reasoning of human language is presented to illustrate the method’s rationality and validity. © The Author(s) 2022 |
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