Proceedings Of Elm 2017

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Proceedings of ELM-2017

Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Proceedings of ELM 2017 Book PDF

Author : Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Publisher : Springer
Page : 340 pages
File Size : 53,7 Mb
Release : 2018-10-16
Category : Technology & Engineering
ISBN : 9783030015206

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Proceedings of ELM-2017 by Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine (ELM) 2017, held in Yantai, China, October 4–7, 2017. The book covers theories, algorithms and applications of ELM. Extreme Learning Machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental `learning particles’ filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. This conference will provide a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. It gives readers a glance of the most recent advances of ELM.

Proceedings of ELM-2014 Volume 1

Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh
Proceedings of ELM 2014 Volume 1 Book PDF

Author : Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh
Publisher : Springer
Page : 446 pages
File Size : 51,6 Mb
Release : 2014-12-04
Category : Technology & Engineering
ISBN : 9783319140636

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Proceedings of ELM-2014 Volume 1 by Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”. The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.

Proceedings of ELM 2018

Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Proceedings of ELM 2018 Book PDF

Author : Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Publisher : Springer
Page : 347 pages
File Size : 47,6 Mb
Release : 2019-06-29
Category : Technology & Engineering
ISBN : 9783030233075

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Proceedings of ELM 2018 by Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2018, which was held in Singapore, November 21–23, 2018. This conference provided a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. Extreme Learning Machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental “learning particles” filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc.) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. The main theme of ELM2018 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning. This book covers theories, algorithms and applications of ELM. It gives readers a glance at the most recent advances of ELM.

Proceedings of ELM-2015 Volume 1

Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Proceedings of ELM 2015 Volume 1 Book PDF

Author : Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Publisher : Springer
Page : 532 pages
File Size : 40,7 Mb
Release : 2015-12-31
Category : Technology & Engineering
ISBN : 9783319283975

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Proceedings of ELM-2015 Volume 1 by Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.

Proceedings of ELM-2014 Volume 2

Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh
Proceedings of ELM 2014 Volume 2 Book PDF

Author : Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh
Publisher : Springer
Page : 0 pages
File Size : 54,7 Mb
Release : 2016-09-29
Category : Technology & Engineering
ISBN : 3319366858

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Proceedings of ELM-2014 Volume 2 by Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”. The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.

Proceedings of ELM-2015 Volume 2

Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Proceedings of ELM 2015 Volume 2 Book PDF

Author : Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Publisher : Springer
Page : 516 pages
File Size : 47,9 Mb
Release : 2016-01-02
Category : Technology & Engineering
ISBN : 9783319283739

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Proceedings of ELM-2015 Volume 2 by Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.

Proceedings of ELM2019

Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Proceedings of ELM2019 Book PDF

Author : Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Publisher : Springer Nature
Page : 189 pages
File Size : 55,5 Mb
Release : 2020-09-11
Category : Technology & Engineering
ISBN : 9783030589899

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Proceedings of ELM2019 by Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2019, which was held in Yangzhou, China, December 14–16, 2019. Extreme Learning Machines (ELMs) aim to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental ‘learning particles’ filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. The main theme of ELM2019 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning. This conference provides a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. This book covers theories, algorithms and applications of ELM. It gives readers a glance of the most recent advances of ELM.

Proceedings of ELM-2016

Jiuwen Cao,Erik Cambria,Amaury Lendasse,Yoan Miche,Chi Man Vong
Proceedings of ELM 2016 Book PDF

Author : Jiuwen Cao,Erik Cambria,Amaury Lendasse,Yoan Miche,Chi Man Vong
Publisher : Springer
Page : 285 pages
File Size : 42,6 Mb
Release : 2017-05-25
Category : Technology & Engineering
ISBN : 9783319574219

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Proceedings of ELM-2016 by Jiuwen Cao,Erik Cambria,Amaury Lendasse,Yoan Miche,Chi Man Vong Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2016, which was held in Singapore, December 13-15, 2016. This conference will provide a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. Extreme Learning Machines (ELM) aims to break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELM represents a suite of (machine or possibly biological) learning techniques in which hidden neurons need not be tuned. ELM learning theories show that very effective learning algorithms can be derived based on randomly generated hidden neurons (with almost any nonlinear piecewise activation functions), independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. ELM offers significant advantages over conventional neural network learning algorithms such as fast learning speed, ease of implementation, and minimal need for human intervention. ELM also shows potential as a viable alternative technique for large‐scale computing and artificial intelligence. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.

Using Computational Intelligence for the Dark Web and Illicit Behavior Detection

Rawat, Romil,Kaur, Upinder,Khan, Shadab Pasha,Sikarwar, Ranjana,Sankaran, K. Sakthidasan
Using Computational Intelligence for the Dark Web and Illicit Behavior Detection Book PDF

Author : Rawat, Romil,Kaur, Upinder,Khan, Shadab Pasha,Sikarwar, Ranjana,Sankaran, K. Sakthidasan
Publisher : IGI Global
Page : 336 pages
File Size : 46,8 Mb
Release : 2022-05-06
Category : Computers
ISBN : 9781668464458

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Using Computational Intelligence for the Dark Web and Illicit Behavior Detection by Rawat, Romil,Kaur, Upinder,Khan, Shadab Pasha,Sikarwar, Ranjana,Sankaran, K. Sakthidasan Pdf

The Dark Web is a known hub that hosts myriad illegal activities behind the veil of anonymity for its users. For years now, law enforcement has been struggling to track these illicit activities and put them to an end. However, the depth and anonymity of the Dark Web has made these efforts difficult, and as cyber criminals have more advanced technologies available to them, the struggle appears to only have the potential to worsen. Law enforcement and government organizations also have emerging technologies on their side, however. It is essential for these organizations to stay up to date on these emerging technologies, such as computational intelligence, in order to put a stop to the illicit activities and behaviors presented in the Dark Web. Using Computational Intelligence for the Dark Web and Illicit Behavior Detection presents the emerging technologies and applications of computational intelligence for the law enforcement of the Dark Web. It features analysis into cybercrime data, examples of the application of computational intelligence in the Dark Web, and provides future opportunities for growth in this field. Covering topics such as cyber threat detection, crime prediction, and keyword extraction, this premier reference source is an essential resource for government organizations, law enforcement agencies, non-profit organizations, politicians, computer scientists, researchers, students, and academicians.

Machine Learning and Deep Learning in Real-Time Applications

Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan
Machine Learning and Deep Learning in Real Time Applications Book PDF

Author : Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan
Publisher : IGI Global
Page : 344 pages
File Size : 46,5 Mb
Release : 2020-04-24
Category : Computers
ISBN : 9781799830979

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Machine Learning and Deep Learning in Real-Time Applications by Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan Pdf

Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

Proceedings of ELM2019

Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Proceedings of ELM2019 Book PDF

Author : Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse
Publisher : Unknown
Page : 0 pages
File Size : 53,6 Mb
Release : 2021
Category : Electronic
ISBN : 3030589900

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Proceedings of ELM2019 by Jiuwen Cao,Chi Man Vong,Yoan Miche,Amaury Lendasse Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2019, which was held in Yangzhou, China, December 14-16, 2019. Extreme Learning Machines (ELMs) aim to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental 'learning particles' filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that "random hidden neurons" capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. The main theme of ELM2019 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning. This conference provides a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. This book covers theories, algorithms and applications of ELM. It gives readers a glance of the most recent advances of ELM.

Forest Microbiology

Fred O Asiegbu,Andriy Kovalchuk
Forest Microbiology Book PDF

Author : Fred O Asiegbu,Andriy Kovalchuk
Publisher : Academic Press
Page : 490 pages
File Size : 41,5 Mb
Release : 2022-07-01
Category : Science
ISBN : 9780323984485

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Forest Microbiology by Fred O Asiegbu,Andriy Kovalchuk Pdf

Forest Microbiology, Volume Two: Forest Tree Health highlights a range of emerging microbial phytopathogens of forest trees, along with novel approaches for managing tree pests and diseases in a changing climate. The book provides an overview of selected microbial pathogens of forest trees, with an emphasis on their biology, lifecycle, spreading mechanisms, impact on affected tree species and current and prospective control strategies. At the same time, the impact of tree microbiomes on host fitness is discussed. Beneficial components of tree microbiota are presented, along with their functional role in tree nutrition, immunity and disease resistance. In addition, this volume addresses the many functions of microbial disease agents of trees including fungi, bacteria, viruses and phytoplasma. Strong emphasis is placed on the genetics, biochemistry, physiology, evolutionary biology and population dynamics of the microorganisms involved. This title is a key resource for foresters and forest pathology practitioners, as well as plant biologists. Provides an overview of selected microbial pathogens of forest trees, with an emphasis on their biology, lifecycle, spreading mechanisms, impact on affected tree species and current and prospective control strategies Highlights novel approaches to managing tree pests and diseases in a changing climate Addresses the many functions of microbial disease agents of trees, including fungi, fungi, bacteria, viruses and phytoplasma

Trends in Functional Programming

Meng Wang,Scott Owens
Trends in Functional Programming Book PDF

Author : Meng Wang,Scott Owens
Publisher : Springer
Page : 149 pages
File Size : 52,6 Mb
Release : 2018-04-18
Category : Computers
ISBN : 9783319897196

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Trends in Functional Programming by Meng Wang,Scott Owens Pdf

This book constitutes the thoroughly refereed revised selected papers of the 18th International Symposium on Trends in Functional Programming, TFP 2017, held in Canterbury, UK, in June 2017. The 8 revised full papers were selected from 16 submissions and present papers in all aspects of functional programming, taking a broad view of current and future trends in the area.

Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence

Rawat, Romil,Telang, Shrikant,William, P.,Kaur, Upinder,C.U., Om Kumar
Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence Book PDF

Author : Rawat, Romil,Telang, Shrikant,William, P.,Kaur, Upinder,C.U., Om Kumar
Publisher : IGI Global
Page : 300 pages
File Size : 53,6 Mb
Release : 2022-05-13
Category : Computers
ISBN : 9781668439449

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Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence by Rawat, Romil,Telang, Shrikant,William, P.,Kaur, Upinder,C.U., Om Kumar Pdf

Data stealing is a major concern on the internet as hackers and criminals have begun using simple tricks to hack social networks and violate privacy. Cyber-attack methods are progressively modern, and obstructing the attack is increasingly troublesome, regardless of whether countermeasures are taken. The Dark Web especially presents challenges to information privacy and security due to anonymous behaviors and the unavailability of data. To better understand and prevent cyberattacks, it is vital to have a forecast of cyberattacks, proper safety measures, and viable use of cyber-intelligence that empowers these activities. Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence discusses cyberattacks, security, and safety measures to protect data and presents the shortcomings faced by researchers and practitioners due to the unavailability of information about the Dark Web. Attacker techniques in these Dark Web environments are highlighted, along with intrusion detection practices and crawling of hidden content. Covering a range of topics such as malware and fog computing, this reference work is ideal for researchers, academicians, practitioners, industry professionals, computer scientists, scholars, instructors, and students.

Application of Machine Learning Models in Agricultural and Meteorological Sciences

Mohammad Ehteram,Akram Seifi,Fatemeh Barzegari Banadkooki
Application of Machine Learning Models in Agricultural and Meteorological Sciences Book PDF

Author : Mohammad Ehteram,Akram Seifi,Fatemeh Barzegari Banadkooki
Publisher : Springer Nature
Page : 201 pages
File Size : 42,8 Mb
Release : 2023-03-21
Category : Computers
ISBN : 9789811997334

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Application of Machine Learning Models in Agricultural and Meteorological Sciences by Mohammad Ehteram,Akram Seifi,Fatemeh Barzegari Banadkooki Pdf

This book is a comprehensive guide for agricultural and meteorological predictions. It presents advanced models for predicting target variables. The different details and conceptions in the modelling process are explained in this book. The models of the current book help better agriculture and irrigation management. The models of the current book are valuable for meteorological organizations. Meteorological and agricultural variables can be accurately estimated with this book's advanced models. Modelers, researchers, farmers, students, and scholars can use the new optimization algorithms and evolutionary machine learning to better plan and manage agriculture fields. Water companies and universities can use this book to develop agricultural and meteorological sciences. The details of the modeling process are explained in this book for modelers. Also this book introduces new and advanced models for predicting hydrological variables. Predicting hydrological variables help water resource planning and management. These models can monitor droughts to avoid water shortage. And this contents can be related to SDG6, clean water and sanitation. The book explains how modelers use evolutionary algorithms to develop machine learning models. The book presents the uncertainty concept in the modeling process. New methods are presented for comparing machine learning models in this book. Models presented in this book can be applied in different fields. Effective strategies are presented for agricultural and water management. The models presented in the book can be applied worldwide and used in any region of the world. The models of the current books are new and advanced. Also, the new optimization algorithms of the current book can be used for solving different and complex problems. This book can be used as a comprehensive handbook in the agricultural and meteorological sciences. This book explains the different levels of the modeling process for scholars.