Disaster Monitoring of Satellite Image Processing Using Progressive Image Classification

The analysis of remote sensing image areas is needed for climate detection and management, especially for monitoring flood disasters in critical environments and applications. Satellites are mostly used to detect disasters on Earth, and they have advantages in capturing Earth images. Using the control technique, Earth images can be used to obtain detailed terrain information. Since the acquisition of satellite and aerial imagery, this system has been able to detect floods, and with increasing convenience, flood detection has become more desirable in the last few years. In this paper, a Big Data Set-based Progressive Image Classification Algorithm (PICA) system is introduced to implement an image processing technique, detect disasters, and determine results with the help of the PICA, which allows disaster analysis to be extracted more effectively. The PICA is essential to overcoming strong shadows, for proper access to disaster characteristics to false positives by operators, and to false predictions that affect the impact of the disaster. The PICA creates tailoring and adjustments obtained from satellite images before training and post-disaster aerial image data patches. Two types of proposed PICA systems detect disasters faster and more accurately (95.6%).     

基于深度学习的自然灾害遥感影像语义分割

自然灾害种类繁多, 通过遥感影像语义分割相对比较困难. 为了能够更好实现遥感影像分割, 本文提出一种基于生成对抗网络的3层遥感影像语义分割模型, 针对不同场景的解析, 基于全卷积神经网络FCN, 设计一种多层次的遥感语义分割框架. 有效对遥感图像语义分割进行处理, 从而提高了模型的分割精度. 实验表明利用这种模型是有效的, 特别是受损建筑的分割结果, mIoU为82.28%, 通过该模型与其他网络模型进行对比, 其性能评价指标明显优于其他网络模型. 最后, 通过对自然灾害各种场景影像进行分析, 为应急管理部门提供一份可靠的数据报告.     

Real time flood disaster monitoring based on energy efficient ensemble clustering mechanism in wireless sensor network

In this article, energy efficient ensemble clustering method (EECM) with black widow optimization (EECM-BWO) algorithm is proposed for effective data transmission with the help of real time flood disaster monitoring wireless sensor network (WSN). Initially, unified scalable ensemble clustering algorithm based on ensemble generation and consensus function is proposed for selecting the optimal routing path among the node using BWO algorithm. Then, biologically inspired routing black widow spiders optimization algorithm is proposed to trade off the nodes energy level, self-organization, and self-configuration in the WSN. The simulation is performed using NS2 simulator for validating the performance of the proposed EECM-BWO method. Here, in node, low delay achieves 24.07%, 72.58%, 51.36%, 81.75%, 77.74%, high packet delivery ratio achieves 70.83%, 53.93%, 90.23%, 43.58%, 24.58%, low packet drop attains 77.93%, 72.76%, 61.56%, 51.87%, 34.35%, low energy consumption attains 75.9%, 52.94%, 65.81%, 58%, 41.2% compared with existing energy-efficient clustering approach consolidated game theory as well as dual-cluster-head mode for WSNs energy-aware clustering by cuckoo optimization approach (EECM-COA), energy-aware clustering-based routing using multi-path reliable transmission with routing and control board (EECM-RCB-MRT), adaptive repair algorithm with temporally ordered routing algorithms for flood control strategy (EECM-AR-TORA-FCS), passive multi-hop clustering algorithm (EECM-PMC), dynamic source routing protocol based on genetic algorithm-bacterial foraging optimization (DSR-GA-BFO).     

白云鄂博铁矿东矿边坡稳定性研究

针对白云鄂博铁矿东矿C区边坡产生的3处不稳定滑体,结合现场工程地质勘察和岩石力学试验,采用理正岩土分析软件5.5版及加拿大岩质边坡稳定性分析计算软件SLIDE5.0对削坡、锚索加固、注浆的二次加固措施进行了分析计算,通过计算得到的安全系数来综合判断该二次加固措施的有效性。分析计算结果表明,通过削坡、锚索加固、注浆的加固措施,可以使白云鄂博铁矿东矿C区边坡最危险滑面的安全系数达到1.186,符合设计边坡稳定安全系数要求。文章最后提出了实施这些措施时的注意事项。     

基于网络检测平台应对网络灾害探讨

网络灾害作为互联网给人类社会带来的各种潜在风险和负面效应之一,正在影响着社会各个行业。除了在网络安全技术、网络道德和相关法律等方面开展研究外,网络检测平台通过检测网络拓扑结构和其他网络动态属性,构建网络地图,可以为网络灾害的预防和控制提供相关依据。     

基于FLAC3D的黄土基底排土场稳定分析

我国大型露天煤矿主要分布在西北部的黄土高原地区,以黄土为基底的排土场形成后,黄土基底的工程性质将发生改变并形成演化弱层,演化弱层对排土场边坡稳定性起到控制作用,由于弱层的存在,边坡容易形成"坐落-滑移式"破坏。本次分析是基于强度折减理论,应用FLAC3D对排土场边坡变形进行数值模拟,展现出排土场边坡变形机理。依据数值模拟结果,获得排土场边坡的最危险滑面和多处潜在滑动面。为排土场边坡失稳的预测及防治工作提供科学依据。     

ARCENGINE 9.2基于visual studio 2005.NET在安徽防灾项目中的应用实例

在防灾项目中,给决策者提供精确的地质地理背景信息,使其随时查询各个地理信息要素是格外必要的,所以项目中的空间数据查询系统发挥着至关重要的作用;该项目中利用AECENGINE9.2的强大嵌入功能和良好的可操作性,基于visual studio 2005.NET使其功能在防灾项目中发挥出来,在地震地质和基础地理两大类中可详尽的查询出地壳等厚线、深断裂构造、遥感地质构造解译图等信息。     

设计的灾难

21世纪是设计的世纪。人类文明发展到今天,设计已经超越原来的艺术或是技术范畴,而是作为现代文明各个方面的交汇点,开始"参与"这个世界。但是,与技术一样,设计本身也是双刃剑,既能给人类文明带来飞跃,也能为人类带来灾难。人类在享受设计成果的同时,更要警惕设计所带来的危机。     

基于CUDA的泥石流模拟计算研究

针对泥石流仿真过程中海量数据计算问题,采用CUDA技术即结合CPU与GPU的优点研究了一种协同计算方法以提高数据计算效率和仿真性能。同时,搭建了基于GPU的泥石流仿真计算平台,对优化的CUDA并行计算方法进行验证。实验结果表明,该方法对海量数据的计算具有快速准确、低成本、低功耗的特点,能为灾害预测提供及时准确的决策支持,满足了高密集型计算的需求。