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Investigation of Flash Floods on Early Basis: A Factual Comprehensive Review

机译:早期调查闪蒸洪水:事实综合评论

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Ultimate extreme flash floods can be acknowledged as a main reason of high casualties and infrastructure loss in many countries like Pakistan, Malaysia, Philippines, Southern France, India, Bangladesh, China, Nepal, Canada, United States of America and others. Run offs can devastate huge buildings and personal belongings within fraction of seconds. Flash floods usually occurs due to many reasons like higher precipitation velocity, melting of ice debris in ocean, high wave current at sea shore, broken reservoir (dam), Cloud to ground flashes, thunderstorm and hurricane inside the ocean. More than one hundred and twenty thousand casualties resulted due to the flash floods during the 1992 and 2005. According to the literature review deadliest flash floods have been observed in past history. Many approaches have been completed to investigate the flash floods accurately and precisely with less false alarm rate. Disaster management authorities are unable to forecast the natural disasters accurately and precisely like tsunami, flash floods, hurricanes and seismic events due to the poor efficiency of the sensors and transmission of missed information. It has also been observed that during the wireless data transmission of sensors to the controller unit some bits of the data are missed, due to these phenomena data is not transmitted properly or indicate the wrong observations. Several diversified approaches have been made to identify the run offs more accurately and precisely. Generally, the approaches can be classified into two categories a) Engineering Based b) Non-Engineering Based. Engineering techniques based on the construction of the dams and reservoirs to store the excess water which causes severe run offs. Designing of various Artificial Intelligence Based competent algorithms to predict the flash floods vigorously can be considered as non-engineering based approaches. Authors have tried their best to summarize and portray all the successful techniques that can be used for the early prediction of flash floods. Scientists can be benefited by this research paper as this research paper is the detailed capsulization of all the approaches that has been carried out for the robust investigation of flash floods. Extensive literature review has been done to observe the comparative analysis for the investigation of flash floods identification accurately. Literature review has been categorized into following types; 1. Sensory Fusion based 2. Artificial Intelligence Based methods 3. Radar and Satellite based approaches 4. Modeling and Nowcasting. According to the exhaustive literature review it can be concluded that swarm intelligence weights optimization for multi-layer perceptron neural network configuration performed better among all the forecasting approaches and recommended as the future enhancement.
机译:最终的极端闪光洪水可以作为巴基斯坦,马来西亚,菲律宾,法国,印度,孟加拉国,中国,尼泊尔,加拿大,美利坚合众国等许多国家等大量伤亡和基础设施损失的主要原因。跑步可以在几秒钟内摧毁巨大的建筑物和个人物品。闪蒸洪水通常由于较多的原因如较高的降水速度,海洋海岸的冰碎片熔化,海岸的高波峰电流,破碎的水库(大坝),云到地面闪烁,雷暴和海洋内部飓风。由于1992年和2005年的闪蒸洪水,超过一百二万伤亡人员导致了一百多万伤亡。根据文献审查在过去的历史中已经观察到最致命的闪蒸洪水。已经完成了许多方法来准确且精确地以较少的误报率来调查闪光洪水。由于传感器的效率差和错过信息的传输,灾害管理机构无法准确且精确地预测自然灾害,并准确且精确地等待自然灾害,如海啸,闪光洪水,飓风和地震事件。还观察到,在对控制器单元的传感器的无线数据传输期间,错过了数据的一些比特,由于这些现象数据未正确发送或指示错误的观察。已经进行了几种多样化的方法来更准确,精确地识别运行。通常,该方法可以分为基于非工程的两类A)。基于坝和储层构建的工程技术,储存过量的水,导致严重的耗尽。基于各种人工智能的主管算法预测闪光洪水的设计可以被认为是非工程的方法。作者已经尽力总结和描绘所有可用于早期预测闪光洪水的成功技术。科学家可以通过本研究论文受益,因为本研究论文是对闪光洪水强劲调查进行的所有方法的详细概括。已经进行了广泛的文献综述,以便准确地观察对闪光洪水型调查的比较分析。文献综述已被分类为以下类型; 1.基于感觉融合2.基于人工智能的方法3.基于雷达和卫星的方法4.建模与垂通。根据详尽的文献回顾,可以得出结论,在所有预测方法中,群体智能权重优化为多层的智能网络配置在所有预测方法中更好地执行,并推荐作为未来的增强。

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