FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2891258839> ?p ?o ?g. }

• W2891258839 endingPage "126" @default.
• W2891258839 startingPage "109" @default.
• W2891258839 abstract "Objective: In this study we propose a fuzzy classifier whose rule antecedents are determined based on the new approach to Clustering with Pairs of Prototypes (CPP). After demonstrating the high generalization ability of the classifier for six various benchmark datasets, a particular emphasis was placed on the application to support fetal state assessment based on the classification of cardiotocographic (CTG) signals. Methods: The CPP is a solution aimed at increasing the performance of fuzzy classifiers by introducing additional prototypes to those obtained using a given basal clustering method. The CPP improvement was achieved by applying the Fuzzy Clustering with ε-Hyperballs (FCεH) as basal clustering, as well as a new ant algorithm-based method of searching for pairs of prototypes. Results: The results were compared with three reference methods: the Lagrangian SVM with the Gaussian kernel function, and the same fuzzy classifier, but using the antecedents determined with the fuzzy c-means and the fuzzy (c+p)-means clustering. In case of five out of six benchmark datasets as well as for the CTG signals classification problem we achieved the highest generalization ability measured with the classification accuracy (benchmark data) and the classification quality index defined as geometric mean of sensitivity and specificity (CTG signals). Conclusions: The results of the numerical experiments showed high accuracy of the CPP-based fuzzy classifier when assessing various types of data. Moreover, the two-step classification of the CTG signals based on the proposed method allows for the efficient signal evaluation aiming to support the automated fetal state assessment. Significance and main impact: The most significant feature of the proposed method is the high generalization ability being the result of the ε-insensitive learning (FCεH clustering), while maintaining the possibility of interpreting the learning outcomes thanks to the linguistic representation of the knowledge in the form of fuzzy conditional (if-then) rules. Therefore, we believe that this solution will have a positive impact on other studies on intelligent systems." @default.
• W2891258839 created "2018-09-27" @default.
• W2891258839 creator A5046487224 @default.
• W2891258839 creator A5059782785 @default.
• W2891258839 creator A5073886028 @default.
• W2891258839 creator A5080671611 @default.
• W2891258839 date "2019-03-01" @default.
• W2891258839 modified "2023-10-16" @default.
• W2891258839 title "Fuzzy classifier based on clustering with pairs of ε-hyperballs and its application to support fetal state assessment" @default.
• W2891258839 cites W1540007258 @default.
• W2891258839 cites W1596717185 @default.
• W2891258839 cites W1607524890 @default.
• W2891258839 cites W1966134891 @default.
• W2891258839 cites W1970104171 @default.
• W2891258839 cites W1982597776 @default.
• W2891258839 cites W1984186688 @default.
• W2891258839 cites W1985702987 @default.
• W2891258839 cites W1988790447 @default.
• W2891258839 cites W1991039395 @default.
• W2891258839 cites W1992176519 @default.
• W2891258839 cites W1999996424 @default.
• W2891258839 cites W2002309500 @default.
• W2891258839 cites W2002863485 @default.
• W2891258839 cites W2014317722 @default.
• W2891258839 cites W2018115628 @default.
• W2891258839 cites W2021449936 @default.
• W2891258839 cites W2024000733 @default.
• W2891258839 cites W2033132936 @default.
• W2891258839 cites W2044050827 @default.
• W2891258839 cites W2046738003 @default.
• W2891258839 cites W2054373203 @default.
• W2891258839 cites W2057094658 @default.
• W2891258839 cites W2064395451 @default.
• W2891258839 cites W2066879661 @default.
• W2891258839 cites W2070154551 @default.
• W2891258839 cites W2070865291 @default.
• W2891258839 cites W2077806522 @default.
• W2891258839 cites W2078749591 @default.
• W2891258839 cites W2079325629 @default.
• W2891258839 cites W2080404350 @default.
• W2891258839 cites W2086929706 @default.
• W2891258839 cites W2107941094 @default.
• W2891258839 cites W2108101782 @default.
• W2891258839 cites W2114296668 @default.
• W2891258839 cites W2116441545 @default.
• W2891258839 cites W2117399799 @default.
• W2891258839 cites W2154929945 @default.
• W2891258839 cites W2155642345 @default.
• W2891258839 cites W2156383341 @default.
• W2891258839 cites W2159265133 @default.
• W2891258839 cites W2159543312 @default.
• W2891258839 cites W2162430466 @default.
• W2891258839 cites W2162800060 @default.
• W2891258839 cites W2168691138 @default.
• W2891258839 cites W2171630164 @default.
• W2891258839 cites W2320602699 @default.
• W2891258839 cites W2324940279 @default.
• W2891258839 cites W2331970566 @default.
• W2891258839 cites W238433468 @default.
• W2891258839 cites W2400383106 @default.
• W2891258839 cites W2477929851 @default.
• W2891258839 cites W2498518426 @default.
• W2891258839 cites W2566250334 @default.
• W2891258839 cites W2579187267 @default.
• W2891258839 cites W2726264666 @default.
• W2891258839 cites W2726354947 @default.
• W2891258839 cites W2761415985 @default.
• W2891258839 cites W2778081019 @default.
• W2891258839 cites W2904084227 @default.
• W2891258839 cites W4211007335 @default.
• W2891258839 cites W4229504348 @default.
• W2891258839 cites W4232380485 @default.
• W2891258839 cites W4237180480 @default.
• W2891258839 cites W4238505001 @default.
• W2891258839 cites W4239510810 @default.
• W2891258839 cites W812518899 @default.
• W2891258839 doi "https://doi.org/10.1016/j.eswa.2018.09.030" @default.
• W2891258839 hasPublicationYear "2019" @default.
• W2891258839 type Work @default.
• W2891258839 sameAs 2891258839 @default.
• W2891258839 citedByCount "13" @default.
• W2891258839 countsByYear W28912588392019 @default.
• W2891258839 countsByYear W28912588392020 @default.
• W2891258839 countsByYear W28912588392021 @default.
• W2891258839 countsByYear W28912588392022 @default.
• W2891258839 countsByYear W28912588392023 @default.
• W2891258839 crossrefType "journal-article" @default.
• W2891258839 hasAuthorship W2891258839A5046487224 @default.
• W2891258839 hasAuthorship W2891258839A5059782785 @default.
• W2891258839 hasAuthorship W2891258839A5073886028 @default.
• W2891258839 hasAuthorship W2891258839A5080671611 @default.
• W2891258839 hasConcept C119857082 @default.
• W2891258839 hasConcept C12267149 @default.
• W2891258839 hasConcept C124101348 @default.
• W2891258839 hasConcept C127385683 @default.
• W2891258839 hasConcept C153180895 @default.
• W2891258839 hasConcept C154945302 @default.
• W2891258839 hasConcept C17212007 @default.

• next