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.
Автор: Li Hong-xing Название: Fuzzy Systems To Quantum Mechanics ISBN: 9811211183 ISBN-13(EAN): 9789811211188 Издательство: World Scientific Publishing Рейтинг: Цена: 22968.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This unique compendium represents important action of fuzzy systems to quantum mechanics. From fuzzy sets to fuzzy systems, it also gives clear descriptions on the development on fuzzy logic, where the most important result is the probability presentation of fuzzy systems.
The important conclusions on fuzzy systems are used in the study of quantum mechanics, which is a very new idea. Eight important conclusions are obtained. The author has proved that mass-point motions in classical mechanics must have waves, which means that any mass-point motion in classical mechanics has wave mass-point dualism as well as any microscopic particle motion must have wave-particle dualism. Based on this conclusion, it has been proven that classical mechanics and quantum mechanics are unified.
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11504.00 р. Наличие на складе: Нет в наличии.
Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
Автор: Management Association Information R. Название: Research Anthology on Artificial Neural Network Applications, VOL 2 ISBN: 1668435802 ISBN-13(EAN): 9781668435809 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 59941.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Management Association Information R. Название: Research Anthology on Artificial Neural Network Applications, VOL 3 ISBN: 1668435810 ISBN-13(EAN): 9781668435816 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 59941.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
This book provides a starting point for software professionals to apply artificial neural networks for software reliability prediction without having analyst capability and expertise in various ANN architectures and their optimization.
Artificial neural network (ANN) has proven to be a universal approximator for any non-linear continuous function with arbitrary accuracy. This book presents how to apply ANN to measure various software reliability indicators: number of failures in a given time, time between successive failures, fault-prone modules and development efforts. The application of machine learning algorithm i.e. artificial neural networks application in software reliability prediction during testing phase as well as early phases of software development process are presented. Applications of artificial neural network for the above purposes are discussed with experimental results in this book so that practitioners can easily use ANN models for predicting software reliability indicators.
Автор: Subana Shanmuganathan; Sandhya Samarasinghe Название: Artificial Neural Network Modelling ISBN: 3319284932 ISBN-13(EAN): 9783319284934 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Artificial Neural Networks Applications: An Introduction.- Order in the Black Box: Consistency And Robustness Of Neuron Activation Of Feed Forward Neural Networks And Its Use In Efficient Optimization Of Network Structure.- Artificial Neural Networks as Models of Robustness in Development And Regeneration: Stability of Memory During Morphological Remodeling.- A Structure Optimization Algorithm of Neural Networks For Pattern Learning from Educational Data.- Stochastic Neural Networks for Modelling Random Processes from Observed Data.- Curvelet Interaction with Artificial Neural Networks.- Hybrid Wavelet Neural Network Approaches.-Quantification of Prediction Uncertainty in Artificial Neural Network Models.- Classifying Calpain Inhibitors for The Treatment of Cataracts: A Self Organising Map (SOM) ANN/KM Approach in Drug Discovery.- Improved Ultrasound Based Computer Aided Diagnosis System for Breast Cancer Using Neural Networks Incorporating a Novel Effective Feature - Degree of Central Regularity of Mass.-SOM Clustering and Modelling of Australian Railway Drivers' Sleep, Wake, Duty Profiles.- A Neural Approach to Electricity Demand Forecasting.- Development of Artificial Intelligence Based Regional Flood Estimation Techniques for Eastern Australia.- Artificial Neural Networks in Precipitation Nowcasting: An Australian Case Study.- Construction of Pmx Concentration Surfaces Using Neural Evolutionary Fuzzy Models of Semi Physical Class.- Application of Artificial Neural Network in Social Media Data Analysis: A Case of Lodging Business in Philadelphia.- Sentiment Analysis on Morphologically Rich Languages - An Artificial Neural Network (ANN) Approach.- Predicting Stock Price Movements with News Sentiment: An Artificial Neural Networks Approach.- Modelling Mode Choice of Individual In Linked Trips with Artificial Neural Networks and Fuzzy Representation.- Artificial Neural Network (ANN) Pricing Model for Natural Rubber Products Based on Climate Dependencies.- A Hybrid Artificial Neural Network (ANN) Approach to Spatial and Non-Spatial Attribute Data Mining: A Case Study Experience.
Автор: Omelianenko Iaroslav Название: Hands-On Neuroevolution with Python ISBN: 183882491X ISBN-13(EAN): 9781838824914 Издательство: Неизвестно Рейтинг: Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book will help you to apply popular neuroevolution strategies to existing neural network designs to improve their performance. It covers practical examples in areas such as games, robotics, and simulation of natural processes, using real-world examples and data sets for your better understanding.
Автор: by Shashi Narayan, Claire Gardent Название: Deep Learning Approaches to Text Production ISBN: 1681737604 ISBN-13(EAN): 9781681737607 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 14276.00 р. Наличие на складе: Нет в наличии.
Описание: Text production has many applications. It is used, for instance, to generate dialogue turns from dialogue moves, verbalise the content of knowledge bases, or generate English sentences from rich linguistic representations, such as dependency trees or abstract meaning representations. Text production is also at work in text-to-text transformations such as sentence compression, sentence fusion, paraphrasing, sentence (or text) simplification, and text summarisation. This book offers an overview of the fundamentals of neural models for text production. In particular, we elaborate on three main aspects of neural approaches to text production: how sequential decoders learn to generate adequate text, how encoders learn to produce better input representations, and how neural generators account for task-specific objectives. Indeed, each text-production task raises a slightly different challenge (e.g, how to take the dialogue context into account when producing a dialogue turn, how to detect and merge relevant information when summarising a text, or how to produce a well-formed text that correctly captures the information contained in some input data in the case of data-to-text generation). We outline the constraints specific to some of these tasks and examine how existing neural models account for them. More generally, this book considers text-to-text, meaning-to-text, and data-to-text transformations. It aims to provide the audience with a basic knowledge of neural approaches to text production and a roadmap to get them started with the related work. The book is mainly targeted at researchers, graduate students, and industrials interested in text production from different forms of inputs.
Описание: 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. The book covers everything from the applications and uses of artificial neural networks to deep learning and non-linear problems.
Автор: Dehuri Satchidananda Et Al Название: Integration Of Swarm Intelligence And Artificial Neural Network ISBN: 9814280143 ISBN-13(EAN): 9789814280143 Издательство: World Scientific Publishing Рейтинг: Цена: 16790.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides a forum for the dissemination of knowledge in both theoretical and applied research on swarm intelligence (SI) and artificial neural network (ANN). This title accelerates interaction between the two bodies of knowledge and fosters a unified development in the next generation of computational model for machine learning.
Описание: The aim of this book is to handle different application problems of science and engineering using expert Artificial Neural Network (ANN). As such, the book starts with basics of ANN along with different mathematical preliminaries with respect to algebraic equations. Then it addresses ANN based methods for solving different algebraic equations viz. polynomial equations, diophantine equations, transcendental equations, system of linear and nonlinear equations, eigenvalue problems etc. which are the basic equations to handle the application problems mentioned in the content of the book. Although there exist various methods to handle these problems, but sometimes those may be problem dependent and may fail to give a converge solution with particular discretization. Accordingly, ANN based methods have been addressed here to solve these problems. Detail ANN architecture with step by step procedure and algorithm have been included. Different example problems are solved with respect to various application and mathematical problems. Convergence plots and/or convergence tables of the solutions are depicted to show the efficacy of these methods. It is worth mentioning that various application problems viz. Bakery problem, Power electronics applications, Pole placement, Electrical Network Analysis, Structural engineering problem etc. have been solved using the ANN based methods.
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