模糊非平稳法预测臭氧浓度水平

Affi Nizar Suksmawati, Retantyo Wardoyo
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引用次数: 1

摘要

空气浓度的组成不是恒定的。它在任何时候都是不断变化的,微小的变化,所以需要不止一次的测量来表示一整天的空气浓度水平。模糊非平稳方法可以克服非恒定环境或由基于时间变量的微小时间变化引起的不确定性。本研究采用非平稳模糊方法,根据温度、湿度、风速等输入变量确定O3浓度水平。测试于9月、10月和11月进行,采用四种含义过程解释,即解释1(经典逻辑)、解释2(经典逻辑)、解释3(代数)和解释3(标准)。9月份的测试结果显示,使用MAPE量的误差百分比倾向为19,10月份的量为25,11月份的量为18。
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Prediction of O3 Concentration Level Using Fuzzy Non-Stationary Method
The composition of air concentration is not constant. It constantly changes with minor changes at any time, so more than one measurement is needed to represent the air concentration level for a full day. The fuzzy non-stationary method can overcome uncertainty in an environment that is not constant or caused by minor temporal changes based on time variables. This study uses a non-stationary fuzzy method to determine the level of O3 concentration based on the input variables of temperature, humidity, and wind speed. The tests were conducted in September, October, and November using four types of implication process interpretation, namely interpretation 1 (classical logic), interpretation 2 (classical logic), interpretation 3 (algebraic), and interpretation 3 (standard). The test results in September showed a tendency for error percentage using the MAPE amount of 19, October's amount of 25, and November's amount of 18.
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