Artificial intelligence-based design of reinforced concrete structures, Hong, Won-kee (dr. Won-kee Hong Is A Professor Of Architectural Engineering At Kyung Hee University, South Korea.)
Автор: Hong, Won-Kee Название: Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures ISBN: 103232368X ISBN-13(EAN): 9781032323688 Издательство: Taylor&Francis Рейтинг: Цена: 168430.00 T Наличие на складе: Нет в наличии. Описание: Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures introduces AI-based Lagrange optimization techniques that can enable more rational engineering decisions for concrete structures while conforming to codes of practice. It shows how objective functions including cost, CO2 emissions, and structural weight of concrete structures are optimized either separately or simultaneously while satisfying constraining design conditions using an ANN-based Lagrange algorithm. Any design target can be adopted as an objective function.
Many optimized design examples are verified by both conventional structural calculations and big datasets. Uniquely applies the new powerful tools of AI to concrete structural design and optimizationMulti-objective functions of concrete structures optimized either separately or simultaneouslyDesign requirements imposed by codes are automatically satisfied by constraining conditionsHeavily illustrated in color with practical design examplesThe book suits undergraduate and graduate students who have an understanding of collegelevel calculus and will be especially beneficial to engineers and contractors who seek to optimize concrete structures.
Without mathematics no science would survive. This especially applies to the engineering sciences which highly depend on the applications of mathematics and mathematical tools such as optimization techniques, finite element methods, differential equations, fluid dynamics, mathematical modelling, and simulation. Neither optimization in engineering, nor the performance of safety-critical system and system security; nor high assurance software architecture and design would be possible without the development of mathematical applications.
De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences (AMEIS) focusses on the latest applications of engineering and information technology that are possible only with the use of mathematical methods. By identifying the gaps in knowledge of engineering applications the AMEIS series fosters the international interchange between the sciences and keeps the reader informed about the latest developments.
Автор: Gouse Baig Mohammad, S. Shitharth, Sachi Nandan Mohanty, Sirisha Potluri Название: Cloud Analytics for Industry 4.0 ISBN: 3110771497 ISBN-13(EAN): 9783110771497 Издательство: Walter de Gruyter Рейтинг: Цена: 192090.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides research on the state-of-the-art methods for data management in the fourth industrial revolution, with particular focus on cloud.based data analytics for digital manufacturing infrastructures. Innovative techniques and methods for secure, flexible and profi table cloud manufacturing will be gathered to present advanced and specialized research in the selected area.
Автор: Wu, Hwai-Chung Название: Strengthening of Concrete Structures Using Fiber Reinforced Polym ISBN: 0081006365 ISBN-13(EAN): 9780081006368 Издательство: Elsevier Science Рейтинг: Цена: 174050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Strengthening of Concrete Structures Using Fiber Reinforced Polymers (FRP): Design, Construction and Practical Applications presents a best practice guide on the structural design and strengthening of bridge structures using advanced Fiber Reinforced Polymer (FRP) composites. The book briefly covers the basic concepts of FRP materials and composite mechanics, while focusing on practical design and construction issues, including inspection and quality control, paying special attention to the differences in various design codes (US, Japan, and Europe) and recommendations. . At present, several design guides from the US, Japan, and Europe are available. These guidelines are often inconsistent and do not cover all necessary design and inspection issues to the same degree of detail. This book provides a critical review and comparison of these guidelines, and then puts forward best practice recommendations, filling a significant gap in the literature, and serving as an important resource for engineers, architects, academics, and students interested in FRP materials and their structural applications. Written from a practitioner's point-of-view, it is a valuable design book for structural engineers all over the world.
Автор: Singh Shamsher Название: Analysis and Design of Frp Reinforced Concrete Structures ISBN: 0071847898 ISBN-13(EAN): 9780071847896 Издательство: McGraw-Hill Рейтинг: Цена: 118970.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Provides a commentary on recent financial policies covering macroeconomic perspectives, monetary-fiscal policies, external sector policies, particularly exchange rate management and gold. The collection will be of interest to the general reader with broad interest in financial policies, and also to policy-makers, opinion makers, banks and financial institutions, academics, and students of finance.
Автор: Rajshree Srivastava, Pradeep Kumar Mallick, Siddha Название: Computational Intelligence for Machine Learning and Healthcare Informatics ISBN: 3110647826 ISBN-13(EAN): 9783110647822 Издательство: Walter de Gruyter Цена: 136310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Автор: Zhang Tsinghua University Press Liyi Название: Blind Equalization in Neural Networks ISBN: 3110449625 ISBN-13(EAN): 9783110449624 Издательство: Walter de Gruyter Цена: 123910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential reference for electrical engineers, computer intelligence researchers and neural scientists.
Автор: Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy Название: Deep Learning: Research and Applications ISBN: 3110670798 ISBN-13(EAN): 9783110670790 Издательство: Walter de Gruyter Цена: 136310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book will focus on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it would provide an insight of deep neural networks in action with illustrative coding examples. Moreover, the book will also provide video demonstrations on each chapter. Deep learning is a new area of machine learning research, which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non immediately related fields, for example between air pressure recordings and english words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g., classification) and/or unsupervised (e.g., pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition. The unique features of this book include: • tutorials on deep learning framework with focus on tensor flow, keras etc. • video demonstration of each chapter for enabling the readers to have a good understanding of the chapter contents. • a score of worked out examples on real life applications. • illustrative diagrams • coding examples
Автор: Aditya Khamparia, Bharat Bhushan, Prajoy Podder, Rubaiyat Hossain Mondal, Sachin Kumar, Victor Hugo C. de Albuquerque Название: Computational Intelligence for Managing Pandemics ISBN: 3110700204 ISBN-13(EAN): 9783110700206 Издательство: Walter de Gruyter Рейтинг: Цена: 159860.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Автор: Ashish Khanna, Nhu Gia Nguyen, Rajshree Srivastava, Siddhartha Bhattacharyya Название: Predictive Intelligence in Biomedical and Health Informatics ISBN: 3110676087 ISBN-13(EAN): 9783110676082 Издательство: Walter de Gruyter Рейтинг: Цена: 136310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.
This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems.
Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications.
Tentative Table of Contents/Topic Coverage:?
- Neural Computation
- Evolutionary Computing Methods
- Neuroscience driven AI Inspired Algorithms
- Biological System based algorithms
- Hybrid and Intelligent Computing Algorithms
- Application of Natural Computing
- Review and State of art analysis of Optimization algorithms
- Molecular and Quantum computing applications
- Swarm Intelligence
- Population based algorithm and other optimizations
Название: Computational Intelligence in Software Modeling ISBN: 3110705435 ISBN-13(EAN): 9783110705430 Издательство: Walter de Gruyter Рейтинг: Цена: 131490.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE
The series Frontiers In Computational Intelligence is envisioned to provide comprehensive coverage and understanding of cutting edge research in computational intelligence. It intends to augment the scholarly discourse on all topics relating to the advances in artifi cial life and machine learning in the form of metaheuristics, approximate reasoning, and robotics. Latest research findings are coupled with applications to varied domains of engineering and computer sciences. This field is steadily growing especially with the advent of novel machine learning algorithms being applied to different domains of engineering and technology. The series brings together leading researchers that intend to continue to advance the field and create a broad knowledge about the most recent research.
Series Editor
Dr. Siddhartha Bhattacharyya, CHRIST (Deemed to be University), Bangalore, India
Editorial Advisory Board
Dr. Elizabeth Behrman, Wichita State University, Kansas, USA
Dr. Goran Klepac
Dr. Leo Mrsic, Algebra University College, Croatia
Dr. Aboul Ella Hassanien, Cairo University, Egypt
Dr. Jan Platos, VSB-Technical University of Ostrava, Czech Republic
Dr. Xiao-Zhi Gao, University of Eastern Finland, Finland
Dr. Wellington Pinheiro dos Santos, Federal University of Pernambuco, Brazil
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