Applications of Artificial Neural Networks for Nonlinear Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applications of Artificial Neural Networks for Nonlinear Data write by Patel, Hiral Ashil. This book was released on 2020-09-25. Applications of Artificial Neural Networks for Nonlinear Data available in PDF, EPUB and Kindle. 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.
Applications of Artificial Neural Networks for Nonlinear Data: Concepts and categorization. Chapter 1. Literature Survey for applications of artificial neural networks ; Chapter 2. Comprehensive modelling of ANN ; Chapter 3. Fundamental categories of artificial neural networks ; Chapter 4. Applications of ANN for agriculture using remote sensed data ; Chapter 5. Classification approach for sentiment analysis using machine learning
Applications of Artificial Neural Networks for Nonlinear Data: Concepts and categorization. Chapter 1. Literature Survey for applications of artificial neural networks ; Chapter 2. Comprehensive modelling of ANN ; Chapter 3. Fundamental categories of artificial neural networks ; Chapter 4. Applications of ANN for agriculture using remote sensed data ; Chapter 5. Classification approach for sentiment analysis using machine learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applications of Artificial Neural Networks for Nonlinear Data: Concepts and categorization. Chapter 1. Literature Survey for applications of artificial neural networks ; Chapter 2. Comprehensive modelling of ANN ; Chapter 3. Fundamental categories of artificial neural networks ; Chapter 4. Applications of ANN for agriculture using remote sensed data ; Chapter 5. Classification approach for sentiment analysis using machine learning write by Hiral Ashil Patel. This book was released on 2021. Applications of Artificial Neural Networks for Nonlinear Data: Concepts and categorization. Chapter 1. Literature Survey for applications of artificial neural networks ; Chapter 2. Comprehensive modelling of ANN ; Chapter 3. Fundamental categories of artificial neural networks ; Chapter 4. Applications of ANN for agriculture using remote sensed data ; Chapter 5. Classification approach for sentiment analysis using machine learning available in PDF, EPUB and Kindle. "This book is a collection of research on the contemporary nature of artificial neural networks and their specific implementations within data analysis"--
Research Anthology on Artificial Neural Network Applications
Research Anthology on Artificial Neural Network Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Research Anthology on Artificial Neural Network Applications write by Management Association, Information Resources. This book was released on 2021-07-16. Research Anthology on Artificial Neural Network Applications available in PDF, EPUB and Kindle. 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.
Artificial Neural Networks for Modelling and Control of Non-Linear Systems
Artificial Neural Networks for Modelling and Control of Non-Linear Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Neural Networks for Modelling and Control of Non-Linear Systems write by Johan A.K. Suykens. This book was released on 2012-12-06. Artificial Neural Networks for Modelling and Control of Non-Linear Systems available in PDF, EPUB and Kindle. Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Among these properties are their universal approximation ability, their parallel network structure and the availability of on- and off-line learning methods for the interconnection weights. However, dynamic models that contain neural network architectures might be highly non-linear and difficult to analyse as a result. Artificial Neural Networks for Modelling and Control of Non-Linear Systems investigates the subject from a system theoretical point of view. However the mathematical theory that is required from the reader is limited to matrix calculus, basic analysis, differential equations and basic linear system theory. No preliminary knowledge of neural networks is explicitly required. The book presents both classical and novel network architectures and learning algorithms for modelling and control. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems. A major contribution of this book is to introduce NLq Theory as an extension towards modern control theory, in order to analyze and synthesize non-linear systems that contain linear together with static non-linear operators that satisfy a sector condition: neural state space control systems are an example. Moreover, it turns out that NLq Theory is unifying with respect to many problems arising in neural networks, systems and control. Examples show that complex non-linear systems can be modelled and controlled within NLq theory, including mastering chaos. The didactic flavor of this book makes it suitable for use as a text for a course on Neural Networks. In addition, researchers and designers will find many important new techniques, in particular NLq emTheory, that have applications in control theory, system theory, circuit theory and Time Series Analysis.
Emerging Capabilities and Applications of Artificial Higher Order Neural Networks
Emerging Capabilities and Applications of Artificial Higher Order Neural Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Emerging Capabilities and Applications of Artificial Higher Order Neural Networks write by Zhang, Ming. This book was released on 2021-02-05. Emerging Capabilities and Applications of Artificial Higher Order Neural Networks available in PDF, EPUB and Kindle. Artificial neural network research is one of the new directions for new generation computers. Current research suggests that open box artificial higher order neural networks (HONNs) play an important role in this new direction. HONNs will challenge traditional artificial neural network products and change the research methodology that people are currently using in control and recognition areas for the control signal generating, pattern recognition, nonlinear recognition, classification, and prediction. Since HONNs are open box models, they can be easily accepted and used by individuals working in information science, information technology, management, economics, and business fields. Emerging Capabilities and Applications of Artificial Higher Order Neural Networks contains innovative research on how to use HONNs in control and recognition areas and explains why HONNs can approximate any nonlinear data to any degree of accuracy, their ease of use, and how they can have better nonlinear data recognition accuracy than SAS nonlinear procedures. Featuring coverage on a broad range of topics such as nonlinear regression, pattern recognition, and data prediction, this book is ideally designed for data analysists, IT specialists, engineers, researchers, academics, students, and professionals working in the fields of economics, business, modeling, simulation, control, recognition, computer science, and engineering research.
