Neural Networks for Hydrological Modeling

Neural Networks for Hydrological Modeling PDF Author: Robert Abrahart
Publisher: CRC Press
ISBN: 0203024117
Category : Science
Languages : en
Pages : 316

Get Book

Book Description
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

Neural Networks for Hydrological Modeling

Neural Networks for Hydrological Modeling PDF Author: Robert Abrahart
Publisher: CRC Press
ISBN: 0203024117
Category : Science
Languages : en
Pages : 316

Get Book

Book Description
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 PDF Author: R.S. Govindaraju
Publisher: Springer Science & Business Media
ISBN: 9401593418
Category : Science
Languages : en
Pages : 338

Get Book

Book Description
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 PDF Author: Wojciech Samek
Publisher: Springer Nature
ISBN: 3030289540
Category : Computers
Languages : en
Pages : 435

Get Book

Book Description
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.

Neural Networks for Hydrological Modeling

Neural Networks for Hydrological Modeling PDF Author: Robert Abrahart
Publisher: CRC Press
ISBN: 9789058096197
Category : Science
Languages : en
Pages : 324

Get Book

Book Description
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.

Advances in Data-Based Approaches for Hydrologic Modeling and Forecasting

Advances in Data-Based Approaches for Hydrologic Modeling and Forecasting PDF Author:
Publisher:
ISBN: 9814464759
Category :
Languages : en
Pages :

Get Book

Book Description


Hydrological Data Driven Modelling

Hydrological Data Driven Modelling PDF Author: Renji Remesan
Publisher: Springer
ISBN: 3319092359
Category : Science
Languages : en
Pages : 250

Get Book

Book Description
This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.

Advances in Data-based Approaches for Hydrologic Modeling and Forecasting

Advances in Data-based Approaches for Hydrologic Modeling and Forecasting PDF Author: Bellie Sivakumar
Publisher: World Scientific
ISBN: 9814307971
Category : Science
Languages : en
Pages : 542

Get Book

Book Description
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.

Artificial Neural Networks in Water Supply Engineering

Artificial Neural Networks in Water Supply Engineering PDF Author: Srinivasa Lingireddy
Publisher: ASCE Publications
ISBN: 9780784475607
Category : Technology & Engineering
Languages : en
Pages : 196

Get Book

Book Description
Prepared by the Water Supply Engineering Technical Committee of the Infrastructure Council of the Environmental and Water Resources Institute of ASCE. This report examines the application of artificial neural network (ANN) technology to water supply engineering problems. Although ANN has rarely been used in in this area, those who have done so report findings that were beyond the capability of traditional statistical and mathematical modeling tools. This report describes the availability of diverse applications, along with the basics of neural network modeling, and summarizes the experiences of groups of researchers around the world who successfully demonstrated significant benefits from using ANN technology in water supply engineering. Topics include: Forecasting salinity levels in River Murray, South Australia; Predicting gastroenteritis rates and waterborne outbreaks; Modeling pH levels in a eutrophic Middle Loire River, France; and ANNs as function approximation tools replacing rigorous mathematical simulation models for analyzing water distribution networks.

Artificial Neural Network Modeling of Water and Wastewater Treatment Processes

Artificial Neural Network Modeling of Water and Wastewater Treatment Processes PDF Author: Ali Reza Khataee
Publisher: Nova Novinka
ISBN: 9781611227819
Category : Neural networks (Computer science)
Languages : en
Pages : 0

Get Book

Book Description
Artificial neural networks (ANNs) are computer based systems that are designed to simulate the learning process of neurons in the human brain. ANNs have been attracting great interest during the last decade as predictive models and pattern recognition. Artificial neural networks possess the ability to "learn" from a set of experimental data without actual knowledge of the physical and chemical laws that govern the system. Therefore, ANNs application in data treatment is high, especially where systems present non-linearities and complex behaviour. This book describes the application of artificial neural networks for modelling of water and wastewater treatment processes.

Artificial Intelligence and Soft Computing — ICAISC 2004

Artificial Intelligence and Soft Computing — ICAISC 2004 PDF Author: Leszek Rutkowski
Publisher: Springer Science & Business Media
ISBN: 3540221239
Category : Computers
Languages : en
Pages : 1233

Get Book

Book Description
This book constitutes the refereed proceedings of the 7th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2004, held in Zakopane, Poland in June 2004. The 172 revised contributed papers presented together with 17 invited papers were carefully reviewed and selected from 250 submissions. The papers are organized in topical sections on neural networks, fuzzy systems, evolutionary algorithms, rough sets, soft computing in classification, image processing, robotics, multiagent systems, problems in AI, intelligent control, modeling and system identification, medical applications, mechanical applications, and applications in various fields.