FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3128332488> ?p ?o ?g. }

• W3128332488 endingPage "012032" @default.
• W3128332488 startingPage "012032" @default.
• W3128332488 abstract "Abundance and biological diversity of phytoplankton communities, investigated in this work, are often used as a marker for the determination of environmental health and fresh water quality. Presently their routine analysis is very time consuming and expensive. A lot of articles are devoted to the development of a system for an in situ automated analysis of phytoplankton properties. However, the applied problems of biology, ecology and, in particular, algology usually are associated with some difficulties due to shortage and/or fuzziness of the experimental data. Hence, while using neural network modelling a set of specific problems can occur. In this article on the base of experimental data several such problems are presented and possible solutions are suggested. In particular, the illogical behavior of classifying neural network is revealed, while studying the biological diversity of cyanobacteria, and the original technique for results validation is presented. This problem is investigated on a set of spectroscopic data, recorded by means of confocal laser scanning microscopy. The generalization quality of the trained model is studied as the main learning parameter. Another problem of shortage dataset is examined in the frames of regression model for bioplankton abundance. This problem is solved by means of feed-forward back-propagation neural networks with two hidden layers. The modelling was carried out on a small experimental selection (only 39 observations were available), despite this, the relatively high determination coefficient was obtained for the training and test samples, while using dropout layout." @default.
• W3128332488 created "2021-02-15" @default.
• W3128332488 creator A5007357236 @default.
• W3128332488 creator A5081729412 @default.
• W3128332488 creator A5083655362 @default.
• W3128332488 date "2020-12-01" @default.
• W3128332488 modified "2023-09-27" @default.
• W3128332488 title "Specific features of feed-forward neural networks application in classification and regression problems in algology" @default.
• W3128332488 cites W1965433882 @default.
• W3128332488 cites W1968576612 @default.
• W3128332488 cites W1981976602 @default.
• W3128332488 cites W1987336542 @default.
• W3128332488 cites W1989016021 @default.
• W3128332488 cites W2017488699 @default.
• W3128332488 cites W2064031858 @default.
• W3128332488 cites W2076236170 @default.
• W3128332488 cites W2088735914 @default.
• W3128332488 cites W2089072974 @default.
• W3128332488 cites W2094950035 @default.
• W3128332488 cites W2095705004 @default.
• W3128332488 cites W2116362148 @default.
• W3128332488 cites W2136585924 @default.
• W3128332488 cites W2170207925 @default.
• W3128332488 cites W2465313687 @default.
• W3128332488 cites W2802392386 @default.
• W3128332488 cites W2986980609 @default.
• W3128332488 doi "https://doi.org/10.1088/1742-6596/1703/1/012032" @default.
• W3128332488 hasPublicationYear "2020" @default.
• W3128332488 type Work @default.
• W3128332488 sameAs 3128332488 @default.
• W3128332488 citedByCount "0" @default.
• W3128332488 crossrefType "journal-article" @default.
• W3128332488 hasAuthorship W3128332488A5007357236 @default.
• W3128332488 hasAuthorship W3128332488A5081729412 @default.
• W3128332488 hasAuthorship W3128332488A5083655362 @default.
• W3128332488 hasBestOaLocation W31283324881 @default.
• W3128332488 hasConcept C105795698 @default.
• W3128332488 hasConcept C119857082 @default.
• W3128332488 hasConcept C124101348 @default.
• W3128332488 hasConcept C134306372 @default.
• W3128332488 hasConcept C136389625 @default.
• W3128332488 hasConcept C138885662 @default.
• W3128332488 hasConcept C152877465 @default.
• W3128332488 hasConcept C154945302 @default.
• W3128332488 hasConcept C169903167 @default.
• W3128332488 hasConcept C177148314 @default.
• W3128332488 hasConcept C177264268 @default.
• W3128332488 hasConcept C18903297 @default.
• W3128332488 hasConcept C194051981 @default.
• W3128332488 hasConcept C199360897 @default.
• W3128332488 hasConcept C2778137410 @default.
• W3128332488 hasConcept C33923547 @default.
• W3128332488 hasConcept C41008148 @default.
• W3128332488 hasConcept C41895202 @default.
• W3128332488 hasConcept C50644808 @default.
• W3128332488 hasConcept C58489278 @default.
• W3128332488 hasConcept C77077793 @default.
• W3128332488 hasConcept C83546350 @default.
• W3128332488 hasConcept C86803240 @default.
• W3128332488 hasConceptScore W3128332488C105795698 @default.
• W3128332488 hasConceptScore W3128332488C119857082 @default.
• W3128332488 hasConceptScore W3128332488C124101348 @default.
• W3128332488 hasConceptScore W3128332488C134306372 @default.
• W3128332488 hasConceptScore W3128332488C136389625 @default.
• W3128332488 hasConceptScore W3128332488C138885662 @default.
• W3128332488 hasConceptScore W3128332488C152877465 @default.
• W3128332488 hasConceptScore W3128332488C154945302 @default.
• W3128332488 hasConceptScore W3128332488C169903167 @default.
• W3128332488 hasConceptScore W3128332488C177148314 @default.
• W3128332488 hasConceptScore W3128332488C177264268 @default.
• W3128332488 hasConceptScore W3128332488C18903297 @default.
• W3128332488 hasConceptScore W3128332488C194051981 @default.
• W3128332488 hasConceptScore W3128332488C199360897 @default.
• W3128332488 hasConceptScore W3128332488C2778137410 @default.
• W3128332488 hasConceptScore W3128332488C33923547 @default.
• W3128332488 hasConceptScore W3128332488C41008148 @default.
• W3128332488 hasConceptScore W3128332488C41895202 @default.
• W3128332488 hasConceptScore W3128332488C50644808 @default.
• W3128332488 hasConceptScore W3128332488C58489278 @default.
• W3128332488 hasConceptScore W3128332488C77077793 @default.
• W3128332488 hasConceptScore W3128332488C83546350 @default.
• W3128332488 hasConceptScore W3128332488C86803240 @default.
• W3128332488 hasLocation W31283324881 @default.
• W3128332488 hasOpenAccess W3128332488 @default.
• W3128332488 hasPrimaryLocation W31283324881 @default.
• W3128332488 hasRelatedWork W163918491 @default.
• W3128332488 hasRelatedWork W2037021038 @default.
• W3128332488 hasRelatedWork W2098436338 @default.
• W3128332488 hasRelatedWork W2752124967 @default.
• W3128332488 hasRelatedWork W2772521755 @default.
• W3128332488 hasRelatedWork W2792951589 @default.
• W3128332488 hasRelatedWork W3090337104 @default.
• W3128332488 hasRelatedWork W3162743360 @default.
• W3128332488 hasRelatedWork W3201070945 @default.
• W3128332488 hasRelatedWork W4280583453 @default.
• W3128332488 hasVolume "1703" @default.
• W3128332488 isParatext "false" @default.
• W3128332488 isRetracted "false" @default.

• next