DEVEDŽIĆ, Goran ;MANIĆ, Miodrag ;TANIKIĆ, Dejan ;IVANOVIĆ, Lozica ;MIRIĆ, Nenad . Conceptual Framework for NPN Logic Based Decision Analysis. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 56, n.6, p. 402-408, october 2017. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/sl/article/conceptual-framework-for-npn-logic-based-decision-analysis/>. Date accessed: 19 nov. 2024. doi:http://dx.doi.org/.
Devedžić, G., Manić, M., Tanikić, D., Ivanović, L., & Mirić, N. (2010). Conceptual Framework for NPN Logic Based Decision Analysis. Strojniški vestnik - Journal of Mechanical Engineering, 56(6), 402-408. doi:http://dx.doi.org/
@article{., author = {Goran Devedžić and Miodrag Manić and Dejan Tanikić and Lozica Ivanović and Nenad Mirić}, title = {Conceptual Framework for NPN Logic Based Decision Analysis}, journal = {Strojniški vestnik - Journal of Mechanical Engineering}, volume = {56}, number = {6}, year = {2010}, keywords = {NPN logic and NPN relations; fuyyz cognitive maps; decision analysis; process planning; }, abstract = {The paper presents the methodology for multicriteria decision analysis based on negative-positive-neutral (NPN) logic, which is an extension of both crisp and fuzzy logic. As the basic modeling framework we use fuzzy cognitive maps (FCM) which are a set of meaningful concepts, connected to form a network, with fuzzy weighted links measuring the strength and direction of effect of cause concept over target concept. Introducing NPN logic to FCM modeling framework provides the possibility to measure, the so-called, side effect of each decision-making path. This information additionally describes under what mutual conditions between concepts FCM settles down in equilibrium. An illustrative example from the real industrial environment related to metal cutting process planning parameters analysis demonstrates the potential of the methodology.}, issn = {0039-2480}, pages = {402-408}, doi = {}, url = {https://www.sv-jme.eu/sl/article/conceptual-framework-for-npn-logic-based-decision-analysis/} }
Devedžić, G.,Manić, M.,Tanikić, D.,Ivanović, L.,Mirić, N. 2010 October 56. Conceptual Framework for NPN Logic Based Decision Analysis. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 56:6
%A Devedžić, Goran %A Manić, Miodrag %A Tanikić, Dejan %A Ivanović, Lozica %A Mirić, Nenad %D 2010 %T Conceptual Framework for NPN Logic Based Decision Analysis %B 2010 %9 NPN logic and NPN relations; fuyyz cognitive maps; decision analysis; process planning; %! Conceptual Framework for NPN Logic Based Decision Analysis %K NPN logic and NPN relations; fuyyz cognitive maps; decision analysis; process planning; %X The paper presents the methodology for multicriteria decision analysis based on negative-positive-neutral (NPN) logic, which is an extension of both crisp and fuzzy logic. As the basic modeling framework we use fuzzy cognitive maps (FCM) which are a set of meaningful concepts, connected to form a network, with fuzzy weighted links measuring the strength and direction of effect of cause concept over target concept. Introducing NPN logic to FCM modeling framework provides the possibility to measure, the so-called, side effect of each decision-making path. This information additionally describes under what mutual conditions between concepts FCM settles down in equilibrium. An illustrative example from the real industrial environment related to metal cutting process planning parameters analysis demonstrates the potential of the methodology. %U https://www.sv-jme.eu/sl/article/conceptual-framework-for-npn-logic-based-decision-analysis/ %0 Journal Article %R %& 402 %P 7 %J Strojniški vestnik - Journal of Mechanical Engineering %V 56 %N 6 %@ 0039-2480 %8 2017-10-24 %7 2017-10-24
Devedžić, Goran, Miodrag Manić, Dejan Tanikić, Lozica Ivanović, & Nenad Mirić. "Conceptual Framework for NPN Logic Based Decision Analysis." Strojniški vestnik - Journal of Mechanical Engineering [Online], 56.6 (2010): 402-408. Web. 19 Nov. 2024
TY - JOUR AU - Devedžić, Goran AU - Manić, Miodrag AU - Tanikić, Dejan AU - Ivanović, Lozica AU - Mirić, Nenad PY - 2010 TI - Conceptual Framework for NPN Logic Based Decision Analysis JF - Strojniški vestnik - Journal of Mechanical Engineering DO - KW - NPN logic and NPN relations; fuyyz cognitive maps; decision analysis; process planning; N2 - The paper presents the methodology for multicriteria decision analysis based on negative-positive-neutral (NPN) logic, which is an extension of both crisp and fuzzy logic. As the basic modeling framework we use fuzzy cognitive maps (FCM) which are a set of meaningful concepts, connected to form a network, with fuzzy weighted links measuring the strength and direction of effect of cause concept over target concept. Introducing NPN logic to FCM modeling framework provides the possibility to measure, the so-called, side effect of each decision-making path. This information additionally describes under what mutual conditions between concepts FCM settles down in equilibrium. An illustrative example from the real industrial environment related to metal cutting process planning parameters analysis demonstrates the potential of the methodology. UR - https://www.sv-jme.eu/sl/article/conceptual-framework-for-npn-logic-based-decision-analysis/
@article{{}{.}, author = {Devedžić, G., Manić, M., Tanikić, D., Ivanović, L., Mirić, N.}, title = {Conceptual Framework for NPN Logic Based Decision Analysis}, journal = {Strojniški vestnik - Journal of Mechanical Engineering}, volume = {56}, number = {6}, year = {2010}, doi = {}, url = {https://www.sv-jme.eu/sl/article/conceptual-framework-for-npn-logic-based-decision-analysis/} }
TY - JOUR AU - Devedžić, Goran AU - Manić, Miodrag AU - Tanikić, Dejan AU - Ivanović, Lozica AU - Mirić, Nenad PY - 2017/10/24 TI - Conceptual Framework for NPN Logic Based Decision Analysis JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 56, No 6 (2010): Strojniški vestnik - Journal of Mechanical Engineering DO - KW - NPN logic and NPN relations, fuyyz cognitive maps, decision analysis, process planning, N2 - The paper presents the methodology for multicriteria decision analysis based on negative-positive-neutral (NPN) logic, which is an extension of both crisp and fuzzy logic. As the basic modeling framework we use fuzzy cognitive maps (FCM) which are a set of meaningful concepts, connected to form a network, with fuzzy weighted links measuring the strength and direction of effect of cause concept over target concept. Introducing NPN logic to FCM modeling framework provides the possibility to measure, the so-called, side effect of each decision-making path. This information additionally describes under what mutual conditions between concepts FCM settles down in equilibrium. An illustrative example from the real industrial environment related to metal cutting process planning parameters analysis demonstrates the potential of the methodology. UR - https://www.sv-jme.eu/sl/article/conceptual-framework-for-npn-logic-based-decision-analysis/
Devedžić, Goran, Manić, Miodrag, Tanikić, Dejan, Ivanović, Lozica, AND Mirić, Nenad. "Conceptual Framework for NPN Logic Based Decision Analysis" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 56 Number 6 (24 October 2017)
Strojniški vestnik - Journal of Mechanical Engineering 56(2010)6, 402-408
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The paper presents the methodology for multicriteria decision analysis based on negative-positive-neutral (NPN) logic, which is an extension of both crisp and fuzzy logic. As the basic modeling framework we use fuzzy cognitive maps (FCM) which are a set of meaningful concepts, connected to form a network, with fuzzy weighted links measuring the strength and direction of effect of cause concept over target concept. Introducing NPN logic to FCM modeling framework provides the possibility to measure, the so-called, side effect of each decision-making path. This information additionally describes under what mutual conditions between concepts FCM settles down in equilibrium. An illustrative example from the real industrial environment related to metal cutting process planning parameters analysis demonstrates the potential of the methodology.