An intelligent slope disaster prediction and monitoring system based on WSN and ANP

Autor:	Li-Chia Kuo, Chi-Hua Chen, Che-I Wu, Hsu-Yang Kung
Rok vydání:	2014
Předmět:	Artificial Intelligence Computer science Typhoon Analytic network process General Engineering Monitoring system Landslide Data mining computer.software_genre Wireless sensor network computer Computer Science Applications
Zdroj:	Expert Systems with Applications. 41:4554-4562
ISSN:	0957-4174
DOI:	10.1016/j.eswa.2013.12.049
Popis:	Taiwan generally has large-scale landslides and torrential rainfall during the typhoon season. As Wireless Sensor Networks (WSN) and mobile communication technologies advance rapidly, state-of-the-art technologies are adopted to build a model to reliably predict and monitor disasters, as well as accumulate environmental variation-related information. By integrating WSN and Analytic Network Process (ANP), this study evaluates the weight of disaster factors that adopt the consistency index of pair comparisons on hillslopes. The weight estimation and classification of disaster factors are based on the K-means model to build the hillslope prediction model. The Portrait-based Disaster Alerting System (PDAS) is designed and implemented using the proposed disaster prediction model. The PDAS adopts Web-GIS to visualize the environmental information. Evaluation results of the system indicate that the proposed prediction model achieves more accurate disaster determination than the conventional method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::32d08113612d9b50e12ea49adc7988ff https://doi.org/10.1016/j.eswa.2013.12.049 Zobrazit plný text záznamu Full Text from ScienceDirect