Comparison between a continuous and a discrete method for the aggregation and deffuzification stages of a TRIGA reactor power fuzzy controller
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Cited by (8)
Union score and fuzzy logic mineral prospectivity mapping using discretized and continuous spatial evidence values
2017, Journal of African Earth SciencesCitation Excerpt :In knowledge-driven MPM, as discussed in the Introduction, discretization of continuous spatial data into classes and assign the same weight to all values in each class (e.g., Carranza and Hale, 2001; Luo and Dimitrakopoulos, 2003; Porwal et al., 2003, 2004, 2006; Carranza, 2008b; McKay and Harris, 2015; Elliott et al., 2016; Ford et al., 2016) represents systemic bias in weighting of evidence of prospectivity. However, as have been shown by Tsoukalas and Uhrig (1997), Nykänen et al. (2008), Yousefi and Carranza (2015a), Yousefi and Nykänen (2016), in other fields of study (e.g., Benitez-Read et al., 2005; Xie et al., 2014), and in this paper, assigning continuous weights does not need discretization of continuous evidential values; thus, bias in weighting of evidence due to simplification of data can be avoided. The method for defining continuous weights (or fuzzy membership values) is generally appropriate for continuous-value spatial data.
Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping
2015, Computers and GeosciencesCitation Excerpt :The important advantages of using modified expected value and continuous fuzzy evidence maps to MPM introduced in this paper are as follows. As mentioned in the Introduction, discretization of continuous values in a map to be used as spatial evidence is not needed in fuzzification because fuzzy evidence layers can be generated by using continuous fuzzy membership values as have been shown in Nykänen et al. (2008), here and in other fields of study (e.g., Clenshaw and Olver, 1984; Sakawa and Yauchi, 1999; Benitez-Read et al., 2005; Narmatha Banu and Devaraj, 2012; Ray, 2012; Guillén-Flores et al., 2013; Silva et al., 2014; Xie et al., 2014). However, it has been a traditional practice in MPM to discretize continuous-value spatial evidence into categorized maps (e.g. Bonham-Carter, 1994; Cheng and Agterberg, 1999; D’Ercole et al., 2000; Knox-Robinson, 2000; Carranza and Hale, 2001; Luo and Dimitrakopoulos 2003; Porwal et al., 2003, 2004, 2006; Rogge et al., 2006; Carranza, 2008; González-Álvarez et al., 2010; Markwitz et al., 2010; Lisitsin et al., 2013).
Applying the computational intelligence paradigm to nuclear power plant operation: A review (1990-2015)
2020, Research Anthology on Artificial Intelligence Applications in SecurityApplication of fuzzy logic for power change rate constraint in core power control at Reaktor TRIGA PUSPATI
2020, IOP Conference Series: Materials Science and EngineeringFuzzy evaluation analysis and extraction of H-N parameters for On-site distribution cable
2019, IET Generation, Transmission and DistributionDesign and implementation of a fuzzy controller for a TRIGA mark III reactor
2012, Science and Technology of Nuclear Installations