Neural Networks for Hydrological Modeling - 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 Neural Networks for Hydrological Modeling write by Robert Abrahart. This book was released on 2004-05-15. Neural Networks for Hydrological Modeling available in PDF, EPUB and Kindle. A new approach to the fast-developing world of neural hydrological modelling, this book is essential reading for academics and researchers in the fields of water sciences, civil engineering, hydrology and physical geography. Each chapter has been written by one or more eminent experts working in various fields of hydrological modelling. The book covers an introduction to the concepts and technology involved, numerous case-studies with practical applications and methods, and finishes with suggestions for future research directions. Wide in scope, this book offers both significant new theoretical challenges and an examination of real-world problem-solving in all areas of hydrological modelling interest.
Neural Networks for Hydrological Modeling
Neural Networks for Hydrological Modeling - 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 Neural Networks for Hydrological Modeling write by Robert Abrahart. This book was released on 2004-05-15. Neural Networks for Hydrological Modeling available in PDF, EPUB and Kindle. A new approach to the fast-developing world of neural hydrological modelling, this book is essential reading for academics and researchers in the fields of water sciences, civil engineering, hydrology and physical geography. Each chapter has been written by one or more eminent experts working in various fields of hydrological modelling. The b
Artificial Neural Networks in Hydrology
Artificial Neural Networks in Hydrology - 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 in Hydrology write by R.S. Govindaraju. This book was released on 2013-03-09. Artificial Neural Networks in Hydrology available in PDF, EPUB and Kindle. R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion with the works of Hopfield (1982) and Rumelhart et al. (1986). Not only did these studies place artificial neural networks on a firmer mathematical footing, but also opened the dOOf to a host of potential applications for this computational tool. Consequently, neural network computing has progressed rapidly along all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the jargon associated with the technical literature on this subject is replete with expressions such as excitation and inhibition of neurons, strength of synaptic connections, learning rates, training, and network experience. ANNs have also been referred to as neurocomputers by people who want to preserve this analogy.
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Explainable AI: Interpreting, Explaining and Visualizing Deep 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 Explainable AI: Interpreting, Explaining and Visualizing Deep Learning write by Wojciech Samek. This book was released on 2019-09-10. Explainable AI: Interpreting, Explaining and Visualizing Deep Learning available in PDF, EPUB and Kindle. The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Advances In Data-based Approaches For Hydrologic Modeling And Forecasting
Advances In Data-based Approaches For Hydrologic Modeling And Forecasting - 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 Advances In Data-based Approaches For Hydrologic Modeling And Forecasting write by Bellie Sivakumar. This book was released on 2010-08-10. Advances In Data-based Approaches For Hydrologic Modeling And Forecasting available in PDF, EPUB and Kindle. This book comprehensively accounts the advances in data-based approaches for hydrologic modeling and forecasting. Eight major and most popular approaches are selected, with a chapter for each — stochastic methods, parameter estimation techniques, scaling and fractal methods, remote sensing, artificial neural networks, evolutionary computing, wavelets, and nonlinear dynamics and chaos methods. These approaches are chosen to address a wide range of hydrologic system characteristics, processes, and the associated problems. Each of these eight approaches includes a comprehensive review of the fundamental concepts, their applications in hydrology, and a discussion on potential future directions.
