Applications of Artificial Neural Networks in Hydrology (abstract) - 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 Applications of Artificial Neural Networks in Hydrology (abstract) write by A. W. Minns. This book was released on 1995. Applications of Artificial Neural Networks in Hydrology (abstract) available in PDF, EPUB and Kindle.
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.
Artificial Neural Networks in Water Supply Engineering
Artificial Neural Networks in Water Supply Engineering - 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 Water Supply Engineering write by Srinivasa Lingireddy. This book was released on 2005-01-01. Artificial Neural Networks in Water Supply Engineering available in PDF, EPUB and Kindle. 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.
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 and Evolutionary Computation in Remote Sensing
Artificial Neural Networks and Evolutionary Computation in Remote Sensing - 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 and Evolutionary Computation in Remote Sensing write by Taskin Kavzoglu. This book was released on 2021-01-19. Artificial Neural Networks and Evolutionary Computation in Remote Sensing available in PDF, EPUB and Kindle. Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images. ANNs are effective in finding underlying relationships and structures within multidimensional datasets. Thanks to new sensors, we have images with more spectral bands at higher spatial resolutions, which clearly recall big data problems. For this purpose, evolutionary algorithms become the best solution for analysis. This book includes eleven high-quality papers, selected after a careful reviewing process, addressing current remote sensing problems. In the chapters of the book, superstructural optimization was suggested for the optimal design of feedforward neural networks, CNN networks were deployed for a nanosatellite payload to select images eligible for transmission to ground, a new weight feature value convolutional neural network (WFCNN) was applied for fine remote sensing image segmentation and extracting improved land-use information, mask regional-convolutional neural networks (Mask R-CNN) was employed for extracting valley fill faces, state-of-the-art convolutional neural network (CNN)-based object detection models were applied to automatically detect airplanes and ships in VHR satellite images, a coarse-to-fine detection strategy was employed to detect ships at different sizes, and a deep quadruplet network (DQN) was proposed for hyperspectral image classification.
