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- W2603669964 abstract "Artificial Neural Networks (ANN) belonging to the ArtificialIntelligence methods play an ever increasing role in modernscience. Developed in the 1950s, inspired by the neuronstructure and the way how human brain works they have beenfinding increasingly powerful and exciting applications in allbranches of science. While via hard model chemical orbiological systems can be exactly described by formulas,equations and the values of parameters, ANN using a soft modelcan do the same even when the exact description is not known oris too complex. ANN are often thought to be somethingmysterious, very difficult to understand and thereforepresented just as a black box. Therefore the principals of ANNwill be explained and their enormous potential for modelling ofa broad range of processes fitting under virtually all areas ofscience will be elucidated. Utilisation of ANN will bedocumented on abundant examples from numerous areas of scienceand chemistry including analytical chemistry which is thespeaker s primary field of expertise. The examples involveapplications in classification, biology, medical diagnosis,forensic science, soft modelling of various chemical processes,QSAR, optimisation, multicomponent analysis, process analysis,and optimization of analytical methods for the determination ofa broad range of analytes including simple ions, antiviraldrugs, pharmaceutical products, antidotes against chemicalweapons, nucleotides, complex peptides/protein mixtures etc." @default.
- W2603669964 created "2017-04-07" @default.
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- W2603669964 date "2009-01-01" @default.
- W2603669964 modified "2023-09-26" @default.
- W2603669964 title "ANN in Science: Entomology., pp. 23-32. In, Havel J. & VaňharaJ., Redes neuronales en Ciencia." @default.
- W2603669964 hasPublicationYear "2009" @default.
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