廖内泥炭地的热信号使用较短的内存对其进行了预测

Ulfa Khaira, Muksin Alfalah, Pikir Claudia Septiani Gulo, Robi Purnomo
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引用次数: 1

摘要

印度尼西亚拥有世界上最大、最多样化的热带森林。数以百万计的印尼人依靠这些森林为生。但最近,森林火灾作为一个环境和经济问题已经成为一个国际关注的问题。森林数量减少的原因之一是森林火灾。森林火灾产生的高颗粒排放物可危及人类健康。为此,有必要采取预防措施。可以采取的一种预防措施是预测热点地区的出现,特别是在森林火灾频发的地区。减少森林火灾的一种方法是利用长短期记忆(LSTM)方法预测泥炭地热点的出现。该研究预测,从2019年8月到2020年1月,廖内省将在未来6个月内出现热点。LSTM能够预测RMSE为363.38的时间序列。
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Prediksi Kemunculan Titik Panas Di Lahan Gambut Provinsi Riau Menggunakan Long Short Term Memory
 Indonesia is blessed with the largest and most diverse tropical forests in the world. Millions of Indonesians depend on these forests for their lives. But lately forest fires have become an international concern as an environmental and economic issue. One of the causes of the decline in the number of forests is forest fires. Forest fires produce high particle emissions which can endanger human health. For this reason, necessary precautions. One prevention that can be done is to predict the emergence of hotspots, especially in areas where forest fires are frequent. One way to reduce forest fires is to predict the emergence of hot spots on peatlands with the Long Short Term Memory (LSTM) method. This study predicts the emergence of hotspots in Riau Province over the next 6 months, from August 2019 to January 2020. LSTM is able to predict time series with RMSE 363.38.
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