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Application of Artificial Neural Networks in Geoinformatics

Application of Artificial Neural Networks in Geoinformatics PDF Author: Saro Lee
Publisher: MDPI
ISBN: 303842742X
Category : Science
Languages : en
Pages : 229

Book Description
This book is a printed edition of the Special Issue "Application of Artificial Neural Networks in Geoinformatics" that was published in Applied Sciences

Application of Artificial Neural Networks in Geoinformatics

Application of Artificial Neural Networks in Geoinformatics PDF Author: Saro Lee
Publisher: MDPI
ISBN: 303842742X
Category : Science
Languages : en
Pages : 229

Book Description
This book is a printed edition of the Special Issue "Application of Artificial Neural Networks in Geoinformatics" that was published in Applied Sciences

Application of Artificial Neural Networks in Geoinformatics

Application of Artificial Neural Networks in Geoinformatics PDF Author: Saro Lee
Publisher:
ISBN: 9783038427414
Category :
Languages : en
Pages :

Book Description
Application of Artificial Neural Networks in Geoinformatics.

Artificial Neural Networks and Evolutionary Computation in Remote Sensing

Artificial Neural Networks and Evolutionary Computation in Remote Sensing PDF Author: Taskin Kavzoglu
Publisher: MDPI
ISBN: 3039438271
Category : Science
Languages : en
Pages : 256

Book Description
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.

Geophysical Applications of Artificial Neural Networks and Fuzzy Logic

Geophysical Applications of Artificial Neural Networks and Fuzzy Logic PDF Author: W. Sandham
Publisher: Springer Science & Business Media
ISBN: 9401702713
Category : Mathematics
Languages : en
Pages : 336

Book Description
The past fifteen years has witnessed an explosive growth in the fundamental research and applications of artificial neural networks (ANNs) and fuzzy logic (FL). The main impetus behind this growth has been the ability of such methods to offer solutions not amenable to conventional techniques, particularly in application domains involving pattern recognition, prediction and control. Although the origins of ANNs and FL may be traced back to the 1940s and 1960s, respectively, the most rapid progress has only been achieved in the last fifteen years. This has been due to significant theoretical advances in our understanding of ANNs and FL, complemented by major technological developments in high-speed computing. In geophysics, ANNs and FL have enjoyed significant success and are now employed routinely in the following areas (amongst others): 1. Exploration Seismology. (a) Seismic data processing (trace editing; first break picking; deconvolution and multiple suppression; wavelet estimation; velocity analysis; noise identification/reduction; statics analysis; dataset matching/prediction, attenuation), (b) AVO analysis, (c) Chimneys, (d) Compression I dimensionality reduction, (e) Shear-wave analysis, (f) Interpretation (event tracking; lithology prediction and well-log analysis; prospect appraisal; hydrocarbon prediction; inversion; reservoir characterisation; quality assessment; tomography). 2. Earthquake Seismology and Subterranean Nuclear Explosions. 3. Mineral Exploration. 4. Electromagnetic I Potential Field Exploration. (a) Electromagnetic methods, (b) Potential field methods, (c) Ground penetrating radar, (d) Remote sensing, (e) inversion.

Artificial Neural Networks in Agriculture

Artificial Neural Networks in Agriculture PDF Author: Sebastian Kujawa
Publisher: Mdpi AG
ISBN: 9783036515809
Category : Technology & Engineering
Languages : en
Pages : 284

Book Description
Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial intelligence methods. Artificial neural networks (ANNs) are one of the most popular tools of this kind. They are widely used in solving various classification and prediction tasks, for some time also in the broadly defined field of agriculture. They can form part of precision farming and decision support systems. Artificial neural networks can replace the classical methods of modelling many issues, and are one of the main alternatives to classical mathematical models. The spectrum of applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible.

On the Use of Artificial Neural Networks in Geo-engineering Applications

On the Use of Artificial Neural Networks in Geo-engineering Applications PDF Author: Chune Huang
Publisher:
ISBN:
Category :
Languages : en
Pages : 304

Book Description


Geographic Information Systems, Spatial Modelling and Policy Evaluation

Geographic Information Systems, Spatial Modelling and Policy Evaluation PDF Author: Manfred M. Fischer
Publisher: Springer Science & Business Media
ISBN: 3642775004
Category : Business & Economics
Languages : en
Pages : 281

Book Description
Geographical Information Systems (GIS) provide an enhanced environment for spatial data processing. The ability of geographic information systems to handle and analyse spatially referenced data may be seen as a major characteristic which distinguishes GIS from information systems developed to serve the needs of business data processing as well as from CAD systems or other systems whose primary objective is map production. This book, which contains contributions from a wide-ranging group of international scholars, demonstrates the progress which has been achieved so far at the interface of GIS technology and spatial analysis and planning. The various contributions bring together theoretical and conceptual, technical and applied issues. Topics covered include the design and use of GIS and spatial models, AI tools for spatial modelling in GIS, spatial statistical analysis and GIS, GIS and dynamic modelling, GIS in urban planning and policy making, information systems for policy evaluation, and spatial decision support systems.

Self-Organising Maps

Self-Organising Maps PDF Author: Pragya Agarwal
Publisher: John Wiley & Sons
ISBN: 9780470021682
Category : Science
Languages : en
Pages : 214

Book Description
Self-Organising Maps: Applications in GI Science brings together the latest geographical research where extensive use has been made of the SOM algorithm, and provides readers with a snapshot of these tools that can then be adapted and used in new research projects. The book begins with an overview of the SOM technique and the most commonly used (and freely available) software; it is then sectioned to look at the different uses of the technique, namely clustering, data mining and cartography, from a range of application-areas in the biophysical and socio-economic environments. Only book that takes SOM algorithm to the GIS and Geography research communities The Editors draw together expert contributors from the UK, Europe, USA, New Zealand, and South Africa Covers a range of techniques in clustering, data mining cartography, all featuring an appropriate case study

Handbook of Neural Computing Applications

Handbook of Neural Computing Applications PDF Author: Alianna J. Maren
Publisher: Academic Press
ISBN: 148326484X
Category : Computers
Languages : en
Pages : 472

Book Description
Handbook of Neural Computing Applications is a collection of articles that deals with neural networks. Some papers review the biology of neural networks, their type and function (structure, dynamics, and learning) and compare a back-propagating perceptron with a Boltzmann machine, or a Hopfield network with a Brain-State-in-a-Box network. Other papers deal with specific neural network types, and also on selecting, configuring, and implementing neural networks. Other papers address specific applications including neurocontrol for the benefit of control engineers and for neural networks researchers. Other applications involve signal processing, spatio-temporal pattern recognition, medical diagnoses, fault diagnoses, robotics, business, data communications, data compression, and adaptive man-machine systems. One paper describes data compression and dimensionality reduction methods that have characteristics, such as high compression ratios to facilitate data storage, strong discrimination of novel data from baseline, rapid operation for software and hardware, as well as the ability to recognized loss of data during compression or reconstruction. The collection can prove helpful for programmers, computer engineers, computer technicians, and computer instructors dealing with many aspects of computers related to programming, hardware interface, networking, engineering or design.

An Information-theoretic Approach to Artificial Neural Networks

An Information-theoretic Approach to Artificial Neural Networks PDF Author: Chih-Chung Kao (Ph. D.)
Publisher:
ISBN:
Category : Geographic information systems
Languages : en
Pages : 144

Book Description