Artificial Neural Networks in Biological and Environmental Analysis

Artificial Neural Networks in Biological and Environmental Analysis PDF Author: Grady Hanrahan
Publisher: CRC Press
ISBN: 1439812594
Category : Mathematics
Languages : en
Pages : 206

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Book Description
Originating from models of biological neural systems, artificial neural networks (ANN) are the cornerstones of artificial intelligence research. Catalyzed by the upsurge in computational power and availability, and made widely accessible with the co-evolution of software, algorithms, and methodologies, artificial neural networks have had a profound

Artificial Neural Networks in Biological and Environmental Analysis

Artificial Neural Networks in Biological and Environmental Analysis PDF Author: Grady Hanrahan
Publisher: CRC Press
ISBN: 1439812594
Category : Mathematics
Languages : en
Pages : 206

Get Book Here

Book Description
Originating from models of biological neural systems, artificial neural networks (ANN) are the cornerstones of artificial intelligence research. Catalyzed by the upsurge in computational power and availability, and made widely accessible with the co-evolution of software, algorithms, and methodologies, artificial neural networks have had a profound

Artificial Neural Networks in Biological and Environmental Analysis

Artificial Neural Networks in Biological and Environmental Analysis PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


Artificial Neural Network Modelling

Artificial Neural Network Modelling PDF Author: Subana Shanmuganathan
Publisher: Springer
ISBN: 3319284959
Category : Technology & Engineering
Languages : en
Pages : 468

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Book Description
This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling.

Proceedings of The 9th MAC 2017

Proceedings of The 9th MAC 2017 PDF Author: group of authors
Publisher: MAC Prague consulting
ISBN: 8088085128
Category : Business & Economics
Languages : en
Pages : 245

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Book Description
The 9th Multidisciplinary Academic Conference in Prague 2017, Czech Republic

Research Anthology on Artificial Neural Network Applications

Research Anthology on Artificial Neural Network Applications PDF Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1668424096
Category : Computers
Languages : en
Pages : 1575

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Book Description
Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.

Soft Computing Techniques in Solid Waste and Wastewater Management

Soft Computing Techniques in Solid Waste and Wastewater Management PDF Author: Rama Rao Karri
Publisher: Elsevier
ISBN: 0323859305
Category : Technology & Engineering
Languages : en
Pages : 524

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Book Description
Soft Computing Techniques in Solid Waste and Wastewater Management is a thorough guide to computational solutions for researchers working in solid waste and wastewater management operations. This book covers in-depth analysis of process variables, their effects on overall efficiencies, and optimal conditions and procedures to improve performance using soft computing techniques. These topics coupled with the systematic analyses described will help readers understand various techniques that can be effectively used to achieve the highest performance. In-depth case studies along with discussions on applications of various soft-computing techniques help readers control waste processes and come up with short-term, mid-term and long-term strategies. Waste management is an increasingly important field due to rapidly increasing levels of waste production around the world. Numerous potential solutions for reducing waste production are underway, including applications of machine learning and computational studies on waste management processes. This book details the diverse approaches and techniques in these fields, providing a single source of information researchers and industry practitioners. It is ideal for academics, researchers and engineers in waste management, environmental science, environmental engineering and computing, with relation to environmental science and waste management. - Provides a comprehensive reference on the implementation of soft computing techniques in waste management, drawing together current research and future implications - Includes detailed algorithms used, enabling authors to understand and appreciate potential applications - Presents relevant case studies in solid and wastewater management that show real-world applications of discussed technologies

Biophysics

Biophysics PDF Author: Roland Glaser
Publisher: Springer Science & Business Media
ISBN: 3642252125
Category : Science
Languages : en
Pages : 424

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Book Description
Biophysics is the science of physical principles underlying all processes of life, including the dynamics and kinetics of biological systems. This fully revised 2nd English edition is an introductory text that spans all steps of biological organization, from the molecular, to the organism level, as well as influences of environmental factors. In response to the enormous progress recently made, especially in theoretical and molecular biophysics, the author has updated the text, integrating new results and developments concerning protein folding and dynamics, molecular aspects of membrane assembly and transport, noise-enhanced processes, and photo-biophysics. The advances made in theoretical biology in the last decade call for a fully new conception of the corresponding sections. Thus, the book provides the background needed for fundamental training in biophysics and, in addition, offers a great deal of advanced biophysical knowledge.

Applications of Artificial Neural Networks for Nonlinear Data

Applications of Artificial Neural Networks for Nonlinear Data PDF Author: Patel, Hiral Ashil
Publisher: IGI Global
ISBN: 1799840433
Category : Computers
Languages : en
Pages : 315

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Book Description
Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and unpredictability. The only technology that can properly handle this form of data is artificial neural networks. These modeling systems present a high level of benefits in analyzing complex data in a proficient manner, yet considerable research on the specific applications of these intelligent components is significantly deficient. Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. While highlighting topics including propagation functions, optimization techniques, and learning methodologies, this book is ideally designed for researchers, statisticians, academicians, developers, scientists, practitioners, students, and educators seeking current research on the use of artificial neural networks in diagnosing and solving nonparametric problems.

Advances in Intelligent Systems and Computing II

Advances in Intelligent Systems and Computing II PDF Author: Natalia Shakhovska
Publisher: Springer
ISBN: 3319705814
Category : Technology & Engineering
Languages : en
Pages : 681

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Book Description
This book reports on new theories and applications in the field of intelligent systems and computing. It covers computational and artificial intelligence methods, as well as advances in computer vision, current issues in big data and cloud computing, computation linguistics, and cyber-physical systems. It also reports on data mining and knowledge extraction technologies, as well as central issues in intelligent information management. Written by active researchers, the respective chapters are based on papers presented at the International Conference on Computer Science and Information Technologies (CSIT 2017), held on September 5–8, 2017, in Lviv, Ukraine; and at two workshops accompanying the conference: one on inductive modeling, jointly organized by the Lviv Polytechnic National University and the National Academy of Science of Ukraine; and another on project management, which was jointly organized by the Lviv Polytechnic National University, the International Project Management Association, the Ukrainian Project Management Association, the Kazakhstan Project Management Association, and Nazarbayev University. Given its breadth of coverage, the book provides academics and professionals with extensive information and a timely snapshot of the field of intelligent systems, and is sure to foster new discussions and collaborations among different groups.

Multivariate Statistical Machine Learning Methods for Genomic Prediction

Multivariate Statistical Machine Learning Methods for Genomic Prediction PDF Author: Osval Antonio Montesinos López
Publisher: Springer Nature
ISBN: 3030890104
Category : Technology & Engineering
Languages : en
Pages : 707

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Book Description
This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.