Bio-Inspired Computing Models and Algorithms

Nonfiction, Computers, Advanced Computing, Engineering, Neural Networks, Artificial Intelligence, General Computing
Cover of the book Bio-Inspired Computing Models and Algorithms by Tao Song, Pan Zheng, Mou Ling Dennis Wong;Xun Wang, World Scientific Publishing Company
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Author: Tao Song, Pan Zheng, Mou Ling Dennis Wong;Xun Wang ISBN: 9789813143197
Publisher: World Scientific Publishing Company Publication: April 5, 2019
Imprint: WSPC Language: English
Author: Tao Song, Pan Zheng, Mou Ling Dennis Wong;Xun Wang
ISBN: 9789813143197
Publisher: World Scientific Publishing Company
Publication: April 5, 2019
Imprint: WSPC
Language: English

Bio-inspired computing (BIC) focuses on the designs and developments of computer algorithms and models based on biological mechanisms and living phenomena. It is now a major subfield of natural computation that leverages on the recent advances in computer science, biology and mathematics.

The ideas provide abundant inspiration to construct high-performance computing models and intelligent algorithms, thus enabling powerful tools to solve real-life problems.

Written by world-renowned researchers, this compendium covers the most influential topics on BIC, where the newly-obtained algorithms, developments and results are introduced and elaborated. The potential and valuable directions for further research are addressed as well.

Contents:

  • A Gentle Introduction to Membrane Systems and Their Computational Properties (Alberto Leporati, Luca Manzoni, Giancarlo Mauri, Antonio E Porreca and Claudio Zandron)
  • Results on Computational Complexity in Bio-inspired Computing (Mario J Pérez-Jiménez, Agustín Riscos-Núñez, Luis Valencia-Cabrera and David Orellana-Martín)
  • Integrative Approaches for Predicting microRNA Function and Prioritizing Disease-Related microRNA Using Biological Interaction Networks (Xuan Zhang and Xiangxiang Zeng)
  • Evolutionary Algorithm for Solving Complex Multiobjective Optimization Problems (Ye Tian and Xingyi Zhang)
  • A Bio-inspired Clustering Model for Anomaly Detection in the Mining Industry (Raymond Chiong, Zhongyi Hu, Zongwen Fan, Yuqing Lin, Stefan Chalup and Antoine Desmet)
  • Picture Generating Models Based on the Splicing Operation (K G Subramanian, G Samdanielthompson and N Gnanamalar David)
  • Fingerprint Minutiae to Fixed-Length Bit-String: A Review of Recent Development (Zhe Jin, Wei-Jing Wong and Andrew Beng Jin Teoh)
  • Platform for Detection of Ultra-DNA Signals (10–18 mol/L) with DNA Probe and Nanomaterials (Xun Wang and Ben Hoo Mook)
  • Deep Autoencoders in Pattern Recognition: A Survey (Junfen Chen, Bojun Xie, Hui Zhang and Junhai Zhai)
  • Genetic Algorithm: From Promiscuity to Monogamy (Ting Yee Lim and Choo Jun Tan)

Readership: Researchers, academics and professionals in artificial intelligence, neural networks, theoretical computer science, bioinformatics and biocomputing.
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View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Bio-inspired computing (BIC) focuses on the designs and developments of computer algorithms and models based on biological mechanisms and living phenomena. It is now a major subfield of natural computation that leverages on the recent advances in computer science, biology and mathematics.

The ideas provide abundant inspiration to construct high-performance computing models and intelligent algorithms, thus enabling powerful tools to solve real-life problems.

Written by world-renowned researchers, this compendium covers the most influential topics on BIC, where the newly-obtained algorithms, developments and results are introduced and elaborated. The potential and valuable directions for further research are addressed as well.

Contents:

Readership: Researchers, academics and professionals in artificial intelligence, neural networks, theoretical computer science, bioinformatics and biocomputing.
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