Application of Artificial Neural Networks in Enzyme Technology

Mohd Basyaruddin Abdul Rahman, Naz Chaibakhsh, Mahiran Basri and Abu Bakar Salleh
Universiti Putra Malaysia, UPM Serdang, Malaysia, and others

Series: Mathematics Research Developments
BISAC: MAT000000

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Volume 10

Issue 1

Volume 2

Volume 3

Special issue: Resilience in breaking the cycle of children’s environmental health disparities
Edited by I Leslie Rubin, Robert J Geller, Abby Mutic, Benjamin A Gitterman, Nathan Mutic, Wayne Garfinkel, Claire D Coles, Kurt Martinuzzi, and Joav Merrick

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Mathematical modeling and simulation is a powerful approach for understanding the complexity and nonlinear behavior of biological systems and identifying natural laws describing their behavior. Computational Intelligence (CI) techniques have been successfully applied to solve problems in the identification and control of biological systems. Artificial Neural Networks (ANNs), in particular, provide an adequate approach in estimating variables from incomplete information and handling nonlinear dynamic systems like enzymatic processes. This book reviews specific applications of ANNs in enzyme technology. Certain practical considerations including utilization of DOE for training the neural networks in enzymatic processes have also been introduced. (Imprint: Nova)

Introduction

Neural Network Contributions in Enzyme Technology

Practical Considerations

Conclusion

References

Index

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