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- W2045887890 abstract "Artificial neural networks (ANNs) are a computing paradigm that can be used as a basis for building intelligent information systems. The purpose of this paper is to provide additional evidence as to the ability of an ANN model to forecast and recognise patterns when auditing financial accounts. The present study examines the predictive ability of an ANN by building models using monthly balances of a manufacturing firm. This study uses backpropagation algorithm as learning algorithm. The monthly balances are considered a time-series and the target is to observe the non-linear dynamics and the relationships between accounts. Furthermore, the certain seeded material errors with signals from the ANN model are investigated. The results achieved indicate that neural networks seem promising for analysing patterns that result in a need for additional investigations of unaudited financial data." @default.
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- W2045887890 date "2000-09-01" @default.
- W2045887890 modified "2023-09-26" @default.
- W2045887890 title "Artificial neural network models for predicting patterns in auditing monthly balances" @default.
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- W2045887890 doi "https://doi.org/10.1057/palgrave.jors.2601014" @default.
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