Bio-Inspired Computing Models and Algorithms - Tao Song & Pan Zheng;Mou Ling Dennis Wong;Xun Wang

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Bio-Inspired Computing Models and Algorithms - Tao Song & Pan Zheng;Mou Ling Dennis Wong;Xun Wang - 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.Bio-Inspired Computing;Nature Computing;Membrane Computing;Biometric;Bioinformatics;Neural Networks;Machine Learning00

Name:Bio-Inspired Computing Models and Algorithms
Image:https://is3-ssl.mzstatic.com/image/thumb/Publication123/v4/a6/8a/06/a68a06ea-fce7-91d3-5aab-bd139abb0c3f/9789813143197.jpg/300x500bb.png
Summary: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.Bio-Inspired Computing;Nature Computing;Membrane Computing;Biometric;Bioinformatics;Neural Networks;Machine Learning00
Vendorname:Ingram DV LLC
Price:$99.99
Title:Bio-Inspired Computing Models and Algorithms - Tao Song & Pan Zheng;Mou Ling Dennis Wong;Xun Wang
Publisher:World Scientific Publishing Company
Link:https://books.apple.com/us/book/bio-inspired-computing-models-and-algorithms/id1469319278?uo=2
Artist:Tao Song & Pan Zheng;Mou Ling Dennis Wong;Xun Wang
Category:Computers
Releasedate:2019-04-05T00:00:00-07:00

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