Advanced Applications For Artificial Neural Networks
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| Author | : Adel El-Shahat |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 298 |
| Release | : 2018-02-28 |
| Genre | : Computers |
| ISBN | : 9535137808 |
In this book, highly qualified multidisciplinary scientists grasp their recent researches motivated by the importance of artificial neural networks. It addresses advanced applications and innovative case studies for the next-generation optical networks based on modulation recognition using artificial neural networks, hardware ANN for gait generation of multi-legged robots, production of high-resolution soil property ANN maps, ANN and dynamic factor models to combine forecasts, ANN parameter recognition of engineering constants in Civil Engineering, ANN electricity consumption and generation forecasting, ANN for advanced process control, ANN breast cancer detection, ANN applications in biofuels, ANN modeling for manufacturing process optimization, spectral interference correction using a large-size spectrometer and ANN-based deep learning, solar radiation ANN prediction using NARX model, and ANN data assimilation for an atmospheric general circulation model.
| Author | : Management Association, Information Resources |
| Publisher | : IGI Global |
| Total Pages | : 1575 |
| Release | : 2021-07-16 |
| Genre | : Computers |
| ISBN | : 1668424096 |
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.
| Author | : Adel El-Shahat |
| Publisher | : |
| Total Pages | : 296 |
| Release | : 2018 |
| Genre | : Electronic computers. Computer science |
| ISBN | : 9789535140573 |
In this book, highly qualified multidisciplinary scientists grasp their recent researches motivated by the importance of artificial neural networks. It addresses advanced applications and innovative case studies for the next-generation optical networks based on modulation recognition using artificial neural networks, hardware ANN for gait generation of multi-legged robots, production of high-resolution soil property ANN maps, ANN and dynamic factor models to combine forecasts, ANN parameter recognition of engineering constants in Civil Engineering, ANN electricity consumption and generation forecasting, ANN for advanced process control, ANN breast cancer detection, ANN applications in biofuels, ANN modeling for manufacturing process optimization, spectral interference correction using a large-size spectrometer and ANN-based deep learning, solar radiation ANN prediction using NARX model, and ANN data assimilation for an atmospheric general circulation model.
| Author | : S. K. Rao |
| Publisher | : Discovery Publishing House Pvt Limited |
| Total Pages | : 0 |
| Release | : 2024-01-04 |
| Genre | : Fiction |
| ISBN | : 9788119523146 |
Artificial neural networks (ANNs) have gained immense popularity and proven to be valuable models for various tasks such as classification, clustering, pattern recognition, and prediction across multiple disciplines. As a type of machine learning (ML) model, ANNs have emerged as strong competitors to conventional regression and statistical models in terms of their utility and effectiveness.This book explores the latest advancements in the field, providing readers with a deeper understanding of their applications and potential. With its practical approach and insightful examples, it is an invaluable resource for researchers and practitioners in the field of artificial intelligence.
| Author | : Do, Quang Hung |
| Publisher | : IGI Global |
| Total Pages | : 275 |
| Release | : 2021-01-08 |
| Genre | : Computers |
| ISBN | : 1799832406 |
In today’s modernized market, various disciplines continue to search for universally functional technologies that improve upon traditional processes. Artificial neural networks are a set of statistical modeling tools that are capable of processing nonlinear data with strong accuracy. Due to their complexity, utilizing their potential was previously seen as a challenge. However, with the development of artificial intelligence, this technology has proven to be an effective and efficient problem-solving method. Artificial Neural Network Applications in Business and Engineering is an essential reference source that illustrates recent advancements of artificial neural networks in various professional fields, accompanied by specific case studies and practical examples. Featuring research on topics such as training algorithms, transportation, and computer security, this book is ideally designed for researchers, students, developers, managers, engineers, academicians, industrialists, policymakers, and educators seeking coverage on modern trends in artificial neural networks and their real-world implementations.
| Author | : Alma Y. Alanis |
| Publisher | : Academic Press |
| Total Pages | : 176 |
| Release | : 2019-03-15 |
| Genre | : Science |
| ISBN | : 0128182474 |
Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications. Presents the current trends for the solution of complex engineering problems that cannot be solved through conventional methods Includes real-life scenarios where a wide range of artificial neural network architectures can be used to solve the problems encountered in engineering Contains all the theory required to use the proposed methodologies for different applications
| Author | : Xingui He |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 240 |
| Release | : 2010-07-05 |
| Genre | : Computers |
| ISBN | : 3540737626 |
For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.
| Author | : Graupe Daniel |
| Publisher | : World Scientific |
| Total Pages | : 440 |
| Release | : 2019-03-15 |
| Genre | : Computers |
| ISBN | : 9811201242 |
The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning.This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of applications of neural networks — demonstrating how such case studies are designed, executed and how their results are obtained.The title is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.
| Author | : Joao Luis Garcia Rosa |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 416 |
| Release | : 2016-10-19 |
| Genre | : Computers |
| ISBN | : 9535127047 |
The idea of simulating the brain was the goal of many pioneering works in Artificial Intelligence. The brain has been seen as a neural network, or a set of nodes, or neurons, connected by communication lines. Currently, there has been increasing interest in the use of neural network models. This book contains chapters on basic concepts of artificial neural networks, recent connectionist architectures and several successful applications in various fields of knowledge, from assisted speech therapy to remote sensing of hydrological parameters, from fabric defect classification to application in civil engineering. This is a current book on Artificial Neural Networks and Applications, bringing recent advances in the area to the reader interested in this always-evolving machine learning technique.
| Author | : Ian Flood |
| Publisher | : ASCE Publications |
| Total Pages | : 300 |
| Release | : 1998-01-01 |
| Genre | : Technology & Engineering |
| ISBN | : 9780784474464 |
Sponsored by the Committee on Expert Systems and Artificial Intelligence of the Technical Council on Computer Practices of ASCE. This report illustrates advanced methods and new developments in the application of artificial neural networks to solve problems in civil engineering.Ø Topics include: Øevaluating new construction technologies; Øusing multi-layeredØartificial neural networkØarchitecture to overcome problems with conventional traffic signal control systems; Øincreasing the computational efficiency of an optimization model; Øpredicting carbonation depth in concrete structures; Ødetecting defects in concrete piles; Øanalyzing pavement systems; Øusing neural network hybrids to select the most appropriate bidders for a construction project; and Øpredicting the Energy Performance Index of residential buildings. ØMany of the ideas and techniques discussed in this book cross across disciplinary boundaries and, therefore, should be of interest to all civil engineers.
