基于机器学习算法的丛林火灾先验识别机制

C. Atheeq, Mohammad Mohammad, Aleem Mohammed
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引用次数: 0

摘要

除了造成可怕的死亡和大量的资源,如许多英亩的林地和住所,森林火灾是对巨大的荒野生物和环境的重大威胁。一直以来,全球范围内相当多的火灾都是由于不同的栖息地和布局造成的。所述事项在相当长的一段时间内一直是调查费用;有相当多的优点集中在可用于测试的安排上,或者可能准备用来确定这个缺点。很长一段时间以来,森林和实际的火焰一直是严重的问题。目前,有各种各样的答案来区分森林火灾。人们正在利用传感器来确定火灾。然而,这种情况不适用于大面积的陆地森林。本文讨论了另一种具有渐进式进展的火焰识别方法。具体来说,我们提出了一个阶段——人工智能。个人电脑的创新策略,确认和下落的烟雾和火灾,根据惰性的照片或图形捕获的相机。追踪火灾的人工智能。准确性依赖于使用数据集值的计算,这些数据集值随后分别划分为各种测试集和训练集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prior Bush Fire Identification Mechanism based on Machine Learning Algorithms
Besides causing awful fatalities resulting in deaths and significant resources like many acres of timberland and dwelling places, forest fires are a significant threat to sound enormous wilderness biologically and environmentally. Consistently, a considerable number of fires around the globe reason debacles to different habitats and layouts. The stated matter has been the investigation premium for a significant length of time; there is a considerable amount of good concentrated on arrangements available for testing or perhaps ready to be utilized to determine this disadvantage. Woods and actual flames have been severe issues for quite some time. Presently, there is a wide range of answers for distinguishing woods fires. Individuals are utilizing sensors to determine the fire. However, this case isn't workable for vast sections of land woods. This paper discusses another fire-recognition methodology with incremental advancements. Specifically, we put forward a stage-Artificial Intelligence. The PC innovation strategies for acknowledgment and whereabouts of smog and fires, in light of the inert photographs or the graphics captured by the cameras. AI for tracing down the fires. The accuracy relies on the calculations that use dataset values later divided in various test and train sets, respectively.
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