Oktaviana, Yessy Vita (2018) Perbandingan antara Kalman Filter dan Fraksional Kalman Filter untuk Estimasi Konsentrasi Polutan pada Masalah Polusi Udara. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Masalah pencemaran udara memberikan pengaruh penting dalam kualitas lingkungan serta proses kehidupan manusia itu sendiri. Gas polutan seperti, Ozon merupakan gas berbahaya karena terbentuk dari reaksi NO_x dengan senyawa organik lainnya (VOCs) yang teremisi dari berbagai sumber. Masalah pencemaran udara dapat dimodelkan dalam bentuk TAPM-CTM (The Air Polution Model with Chemical Transport Model). Model tersebut menunjukkan model konsentrasi polutan di udara yang dipengaruhi oleh koefisien difusi. Metode estimasi digunakan untuk meramalkan konsentrasi polutan di masa yang akan datang dan menjaga stabilitas kualitas udara. Pada penelitian ini, suatu algoritma dikembangkan berdasarkan Kalman Filter dan Fraksional Kalman Filter untuk mengatasi model polutan pada permasalahan pencemaran udara. Fraksional Kalman Filter dikaji untuk orde pertama dan orde kedua. Hasil simulasi yang diperoleh menunjukkan bahwa Fraksional KF lebih baik daripada Kalman Filter, dimana RMSE dari Fraksional KF sedikit lebih kecil daripada Kalman Filter. Sebaliknya untuk waktu komputasinya Fraksional KF lebih lama daripada waktu komputasi Kalman Filter untuk masing-masing waktu iterasi yang berbeda.
=========== Air pollution problem gives important effect in quality environment and quality of human’s life. Air pollution can be caused by nature sources or human activities. Pollutant for example Ozone, a harmful gas formed by NO_x and volatile organic compounds (VOCs) emitted from various sources. The air pollution problem can be modeled by TAPM-CTM (The Air Pollution Model with Chemical Transport Model). The model shows concentration of pollutant in the air. Estimation method can be used for forecast pollutant concentration in future and keep stability of air quality. In this research, an algorithm is developed, based on Kalman Filter and Fractional Kalman Filter to solve the model of air pollution’s problem. Fractional Kalman Filter has been examined for first-order difference and second-order difference. The result of simulation are obtained to show Fractional KF is better than Kalman Filter, because RMSE of Fractional KF is slightly smaller than RMSE of Kalman Filter. But, the computational time of Fractional KF is longer than Kalman Filter for each simulation.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTMa 515.544 Okt p |
| Uncontrolled Keywords: | Model polusi udara; Metode Beda Hingga; Kalman Filter; Kalkulus Fraksional; RMSE; Air Pollution Model; Finite Different Method; Kalman Filter; Fractional Calculus; RMSE. |
| Subjects: | Q Science > QA Mathematics > QA402.3 Kalman filtering. T Technology > TD Environmental technology. Sanitary engineering > TD883.5 Air--Pollution |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Mathematics > 44101-(S2) Master Thesis |
| Depositing User: | Oktaviana Yessy Vita |
| Date Deposited: | 29 Jan 2018 04:44 |
| Last Modified: | 18 Sep 2020 07:07 |
| URI: | http://repository.its.ac.id/id/eprint/50877 |
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