Discussion on “Applying fuzzy theory and genetic algorithm to interpolate precipitation” by C.L. Chang, S.L. Lo, and S.L. Yu

Şen, Zekâi̇

doi:10.1016/j.jhydrol.2006.06.023

Cited by 15 publications

(10 citation statements)

References 12 publications

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“…The authors should have checked and demonstrated the MFs of the input variables whether they are in comfort with the FL principles after the model training. Even in the literature, there are some ANFIS models that include flaws and misinterpretations [2][3]. 5) The authors have three input variables each with three fuzzy sets.…”

mentioning

confidence: 99%

Letter to the Editor-in-Chief

Erdik¹

2008

International Communications in Heat and Mass Transfer

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confidence: 99%

Letter to the Editor-in-Chief

Erdik¹

2008

International Communications in Heat and Mass Transfer

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“…However, they and other potential researchers should consider the fact that for the sake of numerical test concessions in the basic fuzzy logic (FL) philosophy should not be made. Otherwise, misinterpretations, misuses and flaws are encountered (Şen [1,2], Erdik [3,4]). For the improvement and support of the topic the following points are suggested.…”

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confidence: 99%

“…1 has some drawbacks in terms of FL philosophy. First of all, in basic FL principles, the most left and right MFs should have membership degree (MD) equal to 1 (Şen [1,2], Erdik [4]), otherwise they cannot be correct linguistically. However, encircled MFs of Fig.…”

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confidence: 99%

A Discussion on “Application of neuro-fuzzy approach in prediction of runup in swash zone” [Applied Ocean Research (2008), doi:10.1016/j.apor.2008.02.004]

Erdik

2008

Applied Ocean Research

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“…Monotonically increasing and decreasing limbs of MFs are the requirement of normal fuzzy sets. 3) In FL philosophy, the most left and right MFs should have a membership degree equal to 1 [2,3]. However, the rightmost MF, namely H for the input variable, S a has decreasing limbs toward "high" values, which is fully contrary to FL principle [3].…”

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confidence: 99%

“…5) The mechanical application of neuro-fuzzy approach through MATLAB software might induce physical and logical problems in terms of FL philosophy even though the results may seem superior from the numerical tests point of view. In the literature, there are many neuro-fuzzy models that are full of flaws (e.g., two or more geometrically close MFs or illogically produced fuzzy rule combinations among input variables) [2,3]. Hence, insight into the physical and logical configuration of the MFs of the concerned input and output variables and related fuzzy rules according to the FL principles is strictly required at any stage of model development during the training stage.…”

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confidence: 99%

Discussion on “A Wavelet-neuro-fuzzy Combined Approach for Digital Relaying of Transmission Line Faults”

Erdik

Şen

2008

Electric Power Components and Systems

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The use of wavelet-neuro-fuzzy intelligence methodology for depicting digital relaying of transmission line faults is a timely approach, which should be elaborated more with future research along the same line. Power system simulation work by MATLAB software is a very useful tool, but without plausible reasoning, it may lead to mechanical achievements in terms of numerical analysis but might be short of sight when linguistic bases are concerned. It seems that the authors did not consider some basic conceptions underlying the fuzzy logic (FL) principle in their proposed model. They mentioned that usually membership functions (MFs) are chosen somewhat arbitrarily and are fixed in nature, which is not quite right. None of the MFs are fixed in nature, but they are flexible depending on the degree of expert view. They misused some points, especially concerning the MFs, which are fully contrary to the philosophy of FL. We would like to present the following important subjects.1) The authors made a terminological mistake in the their article by stating their fuzzy inference system (FIS) editor as the "Mamadani" approach, which should be the "Mamdani" approach, similar to what is available in the literature [1]. 2) On p. 1390 at the beginning of the last paragraph, it is stated that "Usually S a , S b and S c decreases as the fault distance increases from the source end, as represented in Figures 4(a), 4(b), 4(c) through triangular MF with a decreasing trend." The "decreasing trend" in this statement does not have any relation to the shape of the MF, as implied by the authors. Monotonically increasing and decreasing limbs of MFs are the requirement of normal fuzzy sets. 3) In FL philosophy, the most left and right MFs should have a membership degree equal to 1 [2, 3]. However, the rightmost MF, namely H for the input variable, S a has decreasing limbs toward "high" values, which is fully contrary to FL principle [3]. Therefore, MF H for S a is linguistically incorrect according to FL philosophy. Similar flaws could, of course, be noticed for the MFs of the input variables S b and S c and output variable D. In order to alleviate such situations, it is necessary to have either the rightmost limb of the H fuzzy set equal to 1, or there should be another MF to the right of H MF with the right limb equal to 1.

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Discussion on “Applying fuzzy theory and genetic algorithm to interpolate precipitation” by C.L. Chang, S.L. Lo, and S.L. Yu

Cited by 15 publications

References 12 publications

Letter to the Editor-in-Chief

Letter to the Editor-in-Chief

A Discussion on “Application of neuro-fuzzy approach in prediction of runup in swash zone” [Applied Ocean Research (2008), doi:10.1016/j.apor.2008.02.004]

Discussion on “A Wavelet-neuro-fuzzy Combined Approach for Digital Relaying of Transmission Line Faults”

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