Application of artificial neural networks in geoinformatics / / Saro Lee, editor

• Pubblicazione: Basel : , : MDPI AG - Multidisciplinary Digital Publishing Institute, , [2018]; ©2018
• Descrizione fisica: 1 online resource (228 pages) : illustrations
• Disciplina: 550.285
• Soggetto topico: Geoinformatics; Neural networks (Computer science)
• Persona (resp. second.): LeeSaro
• Nota di contenuto: About the Special Issue Editor v -- Saro Lee -- Editorial for Special Issue: Application of Artificial Neural Networks in Geoinformatics doi: 10.3390/app8010055 1 -- Sunmin Lee, Moung-Jin Lee and Hyung-Sup Jung Data Mining Approaches for Landslide Susceptibility Mapping in Umyeonsan, Seoul, South Korea doi: 10.3390/app7070683 4 Hyun-Joo Oh and Saro Lee -- Shallow Landslide Susceptibility Modeling Using the Data Mining Models Artificial Neural Network and Boosted Tree doi: 10.3390/app7101000 25 -- Saro Lee, Sunmin Lee, Wonkyong Song and Moung-Jin Lee -- Habitat Potential Mapping of Marten (Martes flavigula) and Leopard Cat (Prionailurus bengalensis) in South Korea Using Artificial Neural Network Machine Learning doi: 10.3390/app7090912 39 -- Syyed Adnan Raheel Shah, Tom Brijs, Naveed Ahmad, Ali Pirdavani, Yongjun Shen and Muhammad Aamir Basheer -- Road Safety Risk Evaluation Using GIS-Based Data Envelopment Analysis-Artificial Neural Networks Approach doi: 10.3390/app7090886 54 -- Mustafa Ridha Mezaal, Biswajeet Pradhan, Maher Ibrahim Sameen, Helmi Zulhaidi Mohd Shafri and Zainuddin Md Yusoff -- Optimized Neural Architecture for Automatic Landslide Detection from High-Resolution Airborne Laser Scanning Data doi: 10.3390/app7070730 73 -- Guandong Chen, Yu Li, Guangmin Sun and Yuanzhi Zhang -- Application of Deep Networks to Oil Spill Detection Using Polarimetric Synthetic Aperture Radar Images doi: 10.3390/app7100968 93 -- Jeong-In Hwang, Sung-Ho Chae, Daeseong Kim and Hyung-Sup Jung -- Application of Artificial Neural Networks to Ship Detection from X-Band Kompsat5 Imagery doi: 10.3390/app7090961 108 -- Alessandro Piscini, Vito Romaniello, Christian Bignami and Salvatore Stramondo A New Damage Assessment Method by Means of Neural Network and Multi-Sensor -- Satellite Data doi: 10.3390/app7080781 122 Books MDPI -- Prima Riza Kadavi, Won-Jin Lee and Chang-Wook Lee Analysis of the Pyroclastic Flow Deposits of Mount Sinabung and Merapi Using Landsat -- Imagery and the Artificial Neural Networks Approach doi: 10.3390/app7090935 132 -- Soo-Kyung Kwon, Hyung-Sup Jung, Won-Kyung Baek and Daeseong Kim -- Classification of Forest Vertical Structure in South Korea from Aerial Orthophoto and Lidar Data Using an Artificial Neural Network doi: 10.3390/app7101046 146 -- Giles M. Foody Impacts of Sample Design for Validation Data on the Accuracy of Feedforward Neural -- Network Classification doi: 10.3390/app7090888-- Young-Ji Byon, Jun Su Ha, Chung-Suk Cho, Tae-Yeon Kim and Chan Yeob Yeun -- Real-Time Transportation Mode Identification Using Artificial Neural Networks Enhanced with Mode Availability Layers: A Case Study in Dubai doi: 10.3390/app7090923 174 -- Maher Ibrahim Sameen and Biswajeet Pradhan -- Severity Prediction of Traffic Accidents with Recurrent Neural Networks doi: 10.3390/app7060476 191 -- N ´adia F. Afonso and Jos´e C. M. Pires -- Characterization of Surface Ozone Behavior at Different Regimes doi: 10.3390/app7090944 208.
• Sommario/riassunto: Recently, a need has arisen for prediction techniques that can address a variety of problems by combining methods from the rapidly developing field of machine learning with geoinformation technologies such as GIS, remote sensing, and GPS. As a result, over the last few decades, one particular machine learning technology, known as artificial neural networks, has been successfully applied to a wide range of fields in science and engineering. In addition, the development of computational and spatial technologies has led to the rapid growth of geoinformatics, which specializes in the analysis of spatial information. Thus, recently, artificial neural networks have been applied to geoinformatics and have produced valuable results in the fields of geoscience, environment, natural hazards, natural resources, and engineering. Hence, this Special Issue of the journal Applied Sciences, "Application of Artificial Neural Networks in Geoinformatics," was successfully planned, and we here publish a collection of papers detailing novel contributions that are of relevance to these topics.
• Titolo autorizzato: Application of Artificial Neural Networks in Geoinformatics
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910598030803321
• Lo trovi qui: Univ. Federico II