Using Artificial Neural Networks for Timeseries Smoothing and Forecasting: Case Studies in Economics, Vrbka Jaromнr
Автор: Lennart Svensson, Simo Sarkka Название: Bayesian Filtering and Smoothing ISBN: 1108926649 ISBN-13(EAN): 9781108926645 Издательство: Cambridge Academ Рейтинг: Цена: 5542.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Now in its second edition, this accessible text presents a unified Bayesian treatment of state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models. The book focuses on discrete-time state space models and carefully introduces fundamental aspects related to optimal filtering and smoothing. In particular, it covers a range of efficient non-linear Gaussian filtering and smoothing algorithms, as well as Monte Carlo-based algorithms. This updated edition features new chapters on constructing state space models of practical systems, the discretization of continuous-time state space models, Gaussian filtering by enabling approximations, posterior linearization filtering, and the corresponding smoothers. Coverage of key topics is expanded, including extended Kalman filtering and smoothing, and parameter estimation. The book's practical, algorithmic approach assumes only modest mathematical prerequisites, suitable for graduate and advanced undergraduate students. Many examples are included, with Matlab and Python code available online, enabling readers to implement algorithms in their own projects.
Автор: R. Rosandich Название: Intelligent Visual Inspection ISBN: 1461285100 ISBN-13(EAN): 9781461285106 Издательство: Springer Рейтинг: Цена: 26122.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Automated Visual Inspection Using Artificial Neural Networks explains the application of recently emerging technology in the areas of artificial vision and neural networks to automated visual inspection.
Автор: Stasinopoulos, Mikis D. Rigby, Robert A. Heller, Gillian Z. Voudouris, Vlasios De Bastiani, Fernanda Название: Flexible regression and smoothing ISBN: 0367658062 ISBN-13(EAN): 9780367658069 Издательство: Taylor&Francis Рейтинг: Цена: 7654.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a broad overview of GAMLSS methodology and how it is implemented in R. It includes a comprehensive collection of real data examples, integrated code, and figures to illustrate the methods, and is supplemented by a website.
Автор: Naoko Uchiyama Название: Household Vulnerability and Conditional Cash Transfers ISBN: 9811041024 ISBN-13(EAN): 9789811041020 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book empirically analyzes the vulnerability of poor households in rural areas of Mexico and the effects of the conditional cash transfer (CCT) program called PROGRESA-Oportunidades by adopting the two most recent sets of rural household panel data for 2003 2007.
Автор: Lean Yu; Shouyang Wang; Kin Keung Lai Название: Foreign-Exchange-Rate Forecasting with Artificial Neural Networks ISBN: 1441944044 ISBN-13(EAN): 9781441944047 Издательство: Springer Рейтинг: Цена: 21661.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on forecasting foreign exchange rates via artificial neural networks (ANNs), creating and applying the highly useful computational techniques of Artificial Neural Networks (ANNs) to foreign-exchange rate forecasting.
Описание: This book addresses the automatic sizing and layout of analog integrated circuits (ICs) using deep learning (DL) and artificial neural networks (ANN). It explores an innovative approach to automatic circuit sizing where ANNs learn patterns from previously optimized design solutions. In opposition to classical optimization-based sizing strategies, where computational intelligence techniques are used to iterate over the map from devices’ sizes to circuits’ performances provided by design equations or circuit simulations, ANNs are shown to be capable of solving analog IC sizing as a direct map from specifications to the devices’ sizes. Two separate ANN architectures are proposed: a Regression-only model and a Classification and Regression model. The goal of the Regression-only model is to learn design patterns from the studied circuits, using circuit’s performances as input features and devices’ sizes as target outputs. This model can size a circuit given its specifications for a single topology. The Classification and Regression model has the same capabilities of the previous model, but it can also select the most appropriate circuit topology and its respective sizing given the target specification. The proposed methodology was implemented and tested on two analog circuit topologies.
Описание: Covers a range of topics in the field with perspectives, models, and first-hand experiences shared by researchers, discussing applications of artificial neural networks and machine learning for biomedical and business applications and a listing of current open-source software for neural networks, machine learning, and artificial intelligence.
Описание: Covers a range of topics in the field with perspectives, models, and first-hand experiences shared by researchers, discussing applications of artificial neural networks and machine learning for biomedical and business applications and a listing of current open-source software for neural networks, machine learning, and artificial intelligence.
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