Applications of Artificial Neural Networks for Nonlinear Data, Patel Hiral Ashil, Kumar A. V. Senthil
Автор: Patel Hiral Ashil, Kumar A. V. Senthil Название: Applications of Artificial Neural Networks for Nonlinear Data ISBN: 1799851508 ISBN-13(EAN): 9781799851509 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 23199.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. The book highlights a wide range of topics, including propagation functions, optimization techniques, and learning methodologies.
Автор: Alanis, Alma Название: Artificial Neural Networks for Engineering Applications ISBN: 0128182474 ISBN-13(EAN): 9780128182475 Издательство: Elsevier Science Рейтинг: Цена: 17180.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Hoe bestuur je een wendbare organisatie, of beter, hoe bestuur je een organisatie naar een blijvende wendbare organisatie?¢ Ben jij lid van het Managementteam (MT) of lid van de directie die de noodzaak tot verandering in besturing ziet, die de urgentie voelt om daar iets aan te doen en gehoor hiervoor wil vinden bij de collega leden van het MT of directie? ¢ Ben jij een coach in een organisatie die beweging richting een wendbare organisatie vooral bottom up ziet groeien, een beweging waar je de top down beweging aan toe wil voegen?. In deze pocketguide vind je een praktische methode hoe dit aan te pakken. Besturen in een steeds sneller veranderende wereld. Met de waan van de dag die vaak veel aandacht vraagt en die je kan afleiden van de te behalen resultaten. De auteurs gaan in op het operationaliseren van de strategische organisatiedoelen en daarmee het besturen van de gehele organisatie. De stellingname van dit boek is: maak scherp wat dit kwartaal bereikt moet worden om de strategische doelen te bereiken. Stuur kort cyclisch om te kunnen reageren op veranderende klantwensen of gewijzigde wet- en regelgeving. Werk samen als managementteam of directie richting dje strategische doelen en voorkom dat iedereen in de organisatie vooral een eigen doel nastreeft. Breng meer focus in de operationalisering van de strategie, minder met "brandjes" bezig zijn en meer met het voorkomen ervan. Krijg snel helder wat je medewerkers belemmert in hun werk. Lukt het om de belemmeringen in jouw organisatie snel op te lossen? De kern van deze pocketguide betreft het FOCUS- bord. Deze manier van visual management is een krachtig middel in de besturing. De toepassing ervan zorgt voor samenwerking tussen alle lagen in de organisatie, kort cyclisch sturen en focus op het behalen van de strategische doelen.
Описание: This volume contains papers presented at the Third Annual SNN Symposium on Neural Networks held in Nijmegen, 1995. It summarizes developments in neurobiology, the cognitive sciences, robotics, and vision and data modelling. Working neural network solutions to industrial problems are also presented.
Описание: While cognitive informatics and natural intelligence are receiving greater attention by researchers, multidisciplinary approaches still struggle with fundamental problems involving psychology and neurobiological processes of the brain. Examining the difficulties of certain approaches using the tools already available is vital for propelling knowledge forward and making further strides.
Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence is a collection of innovative research that examines the enhancement of human cognitive performance using emerging technologies. Featuring research on topics such as parallel computing, neuroscience, and signal processing, this book is ideally designed for engineers, computer scientists, programmers, academicians, researchers, and students.
Автор: Karthikrajan Senthilnathan, Balamurugan Shanmugam, Dinesh Goyal, Iyswarya Annapoorani, Ravi Samikannu Название: Deep Learning Applications and Intelligent Decision Making in Engineering ISBN: 1799821080 ISBN-13(EAN): 9781799821083 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 32987.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process.
Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.
Автор: Karthikrajan Senthilnathan, Balamurugan Shanmugam, Dinesh Goyal, Iyswarya Annapoorani, Ravi Samikannu Название: Deep Learning Applications and Intelligent Decision Making in Engineering ISBN: 1799821099 ISBN-13(EAN): 9781799821090 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 24948.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is designed for engineers, computer scientists, programmers, software engineers, researchers, academics, and students.
Описание: While cognitive informatics and natural intelligence are receiving greater attention by researchers, multidisciplinary approaches still struggle with fundamental problems involving psychology and neurobiological processes of the brain. Examining the difficulties of certain approaches using the tools already available is vital for propelling knowledge forward and making further strides.
Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence is a collection of innovative research that examines the enhancement of human cognitive performance using emerging technologies. Featuring research on topics such as parallel computing, neuroscience, and signal processing, this book is ideally designed for engineers, computer scientists, programmers, academicians, researchers, and students.
Описание: Artificial intelligence is at the forefront of research and implementation in many industries including healthcare and agriculture. Whether it's detecting disease or generating algorithms, deep learning techniques are advancing exponentially. Researchers and professionals need a platform in which they can keep up with machine learning trends and their developments in the real world.
The Handbook of Research on Applications and Implementations of Machine Learning Techniques provides innovative insights into the multi-disciplinary applications of machine learning algorithms for data analytics. The content within this publication examines disease identification, neural networks, and language support. It is designed for IT professionals, developers, data analysts, technology specialists, R&D professionals, industrialists, practitioners, researchers, academicians, and students seeking research on deep learning procedures and their enactments in the fields of medicine, engineering, and computer science.
Get a head start in the world of AI and deep learning by developing your skills with PyTorch
Key Features
Learn how to define your own network architecture in deep learning
Implement helpful methods to create and train a model using PyTorch syntax
Discover how intelligent applications using features like image recognition and speech recognition really process your data
Book Description
Want to get to grips with one of the most popular machine learning libraries for deep learning? The Deep Learning with PyTorch Workshop will help you do just that, jumpstarting your knowledge of using PyTorch for deep learning even if you're starting from scratch.
It's no surprise that deep learning's popularity has risen steeply in the past few years, thanks to intelligent applications such as self-driving vehicles, chatbots, and voice-activated assistants that are making our lives easier. This book will take you inside the world of deep learning, where you'll use PyTorch to understand the complexity of neural network architectures.
The Deep Learning with PyTorch Workshop starts with an introduction to deep learning and its applications. You'll explore the syntax of PyTorch and learn how to define a network architecture and train a model. Next, you'll learn about three main neural network architectures - convolutional, artificial, and recurrent - and even solve real-world data problems using these networks. Later chapters will show you how to create a style transfer model to develop a new image from two images, before finally taking you through how RNNs store memory to solve key data issues.
By the end of this book, you'll have mastered the essential concepts, tools, and libraries of PyTorch to develop your own deep neural networks and intelligent apps.
What you will learn
Explore the different applications of deep learning
Understand the PyTorch approach to building neural networks
Create and train your very own perceptron using PyTorch
Solve regression problems using artificial neural networks (ANNs)
Handle computer vision problems with convolutional neural networks (CNNs)
Perform language translation tasks using recurrent neural networks (RNNs)
Who this book is for
This deep learning book is ideal for anyone who wants to create and train deep learning models using PyTorch. A solid understanding of the Python programming language and its packages will help you grasp the topics covered in the book more quickly.
Описание: 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.
Описание: 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.
Автор: Quang Hung Do Название: Artificial Neural Network Applications in Business and Engineering ISBN: 1799832392 ISBN-13(EAN): 9781799832393 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 32155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
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