How governance mechanisms in family firms impact open innovation choices: A fuzzy logic approach

2019 ◽  
Vol 28 (4) ◽  
pp. 486-500 ◽  
Author(s):  
Luisa Pellegrini ◽  
Valentina Lazzarotti
Keyword(s):  
Fuzzy Logic ◽  
Open Innovation ◽  
Family Firms ◽  
Governance Mechanisms ◽  
Fuzzy Logic Approach ◽  
Logic Approach

Computing the Probability of Target Detection in Dyanmic Visual Scenes Containing Clutter Using Fuzzy Logic Approach

1998 ◽  
Author(s):  
Thomas Meitzler ◽  
Regina Kistner ◽  
Bill Pibil ◽  
Euijung Sohn ◽  
Darryl Bryk ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Target Detection ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Visual Scenes

Fuzzy logic approach for knowledge modeling in an Ontology: A review

2020 ◽  
Author(s):  
Abdoul Azize Kindo ◽  
Guidedi Kaladzavi ◽  
Sadouanouan Malo ◽  
Gaoussou Camara ◽  
Theodore Marie Yves Tapsoba ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Knowledge Modeling ◽  
Fuzzy Logic Approach ◽  
Logic Approach

Detecting environmental regimes in fish stock-recruitment relationships by fuzzy logic

2001 ◽  
Vol 58 (11) ◽  
pp. 2139-2148 ◽  
Author(s):  
D G Chen
Keyword(s):  
Fuzzy Logic ◽  
Environmental Variable ◽  
Clupea Harengus ◽  
Fish Stock ◽  
Environmental Regimes ◽  
Fuzzy Logic Approach ◽  
Stock Recruitment ◽  
Logic Approach ◽  
Traditional Approaches ◽  
The Impact

A fuzzy logic approach is developed to model and test the impact of environmental regimes on fish stock–recruitment relationships. Traditional methods use environmental variables to classify stock–recruitment data into different membership percentiles followed by fitting the stock–recruitment models for each subset. In contrast, the fuzzy logic approach uses a continuous membership function to provide a rational basis for the classification. Thus, parameter estimation is based on a more logically consistent foundation without resorting to subjective partitions. This new approach is applied to herring stock from the west coast of Vancouver Island (Clupea harengus pallasi) using sea surface temperature as the environmental variable and to Pacific halibut stock (Hippoglossus stenolepis) using the Pacific Decadal Oscillation as the environmental variable. From these applications, the herring stock–recruitment relationships were found to vary significantly during different regimes, whereas this was not the case for halibut. However, in both instances, the fuzzy logic approach demonstrated that density-dependent effects differed between regimes. The fuzzy logic model consistently outperformed traditional approaches as measured by several diagnostic criteria. Because fuzzy logic models address uncertainty better than traditional approaches, they have the potential to improve our ability to understand factors influencing stock–recruitment relationships and thereby manage fisheries more effectively.

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