A method of constructing geo-object ontology in disaster system for prevention and decrease

2009 ◽  
Author(s):  
Bin Li ◽  
Jiping Liu ◽  
Lihong Shi ◽  
Zhenfeng Wang
Keyword(s):  
Object Ontology ◽  
Disaster System

scholarly journals Region-Based Image Retrieval Using an Object Ontology and Relevance Feedback

2004 ◽  
Vol 2004 (6) ◽  
Author(s):  
Vasileios Mezaris ◽  
Ioannis Kompatsiaris ◽  
Michael G. Strintzis
Keyword(s):  
Image Retrieval ◽  
Relevance Feedback ◽  
Object Ontology

Research on the Algorithm of Prevention Forest Fire Disaster in the Poyang Lake Ecological Economic Zone

2012 ◽  
Vol 518-523 ◽  
pp. 5257-5260 ◽  
Author(s):  
Ying Lian Wang ◽  
Jun Yao Ye
Keyword(s):  
Forest Fire ◽  
Clustering Algorithm ◽  
Poyang Lake ◽  
Ecological Economic ◽  
Fire Disaster ◽  
Economic Zone ◽  
The Time Domain ◽  
Forest Fire Disaster ◽  
Disaster System ◽  
Suspicious Area

Poyang Lake Ecological Economic Zone has large forest area, so it's very important to construct prevention forest fire disaster system. This paper presents an algorithm for prevention forest fire disaster based on digital image processing technology. The algorithm distinguishes the realtime forest video by smoke and fire. To determine whether there are some suspicious area in the image in the spatial domain by judging the color properties of smoke and fire through Clustering Algorithm. If it detects any suspicious circumstances, then fixes ccd and detects the suspicious areas in the time domain. In this step, firstly get the initial detect results by wavelet decomposition , then use the k-means clustering algorithm for the spread detection of smoke. Experimental results show that the algorithm is ideal for the experimental video. It alarms before the fire disaster occurs to avoid major fire disaster, which protects the forest resources in the Poyang Lake Ecological Economic Zone.

FOUR MODELS TO CALCULATE A FUZZY PROBABILITY DISTRIBUTION WITH A SMALL SAMPLE

2007 ◽  
Vol 06 (04) ◽  
pp. 611-623 ◽  
Author(s):  
CHONGFU HUANG ◽  
TIAN ZONG ◽  
ZHIFEN CHEN
Keyword(s):  
Probability Distribution ◽  
Natural Disaster ◽  
Small Sample ◽  
Fuzzy Probability ◽  
System Calls ◽  
Fuzzy Methods ◽  
Disaster System

The need to cope with complicated natural disaster system calls for a sophisticated way of analyzing it with the help of fuzzy methods. Therefore, four models are suggested succeedingly to represent a fuzzy probability distribution with a small sample. In this paper, we inspect the four models in detail and evaluate their performance on an emulation test.

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