scholarly journals Black Box Modelling and Simulating the Dynamic Indoor Air Temperature of a Laboratory Using the Continuous-Time Transfer Function Model

Author(s):  
Shamsul Faisal Mohd Hussein ◽  
Noor Bazila Sharifmuddin ◽  
Mohd. Fitri Alif Mohd. Kasai ◽  
Abdulqader Omar Al-Rabeei ◽  
Amrul Faruq ◽  
...  
CAUCHY ◽  
2017 ◽  
Vol 5 (1) ◽  
pp. 29
Author(s):  
Priska Arindya Purnama

The aim of this research is to model and forecast the rainfall in Batu City using multi input transfer function model based on air temperature, humidity, wind speed and cloud. Transfer function model is a multivariate time series model which consists of an output series (Y<sub>t</sub>) sequence expected to be effected by an input series (X<sub>t</sub>) and other inputs in a group called a noise series (N<sub>t</sub>). Multi input transfer function model obtained is (<em>b<sub>1</sub>,s<sub>1</sub>,r<sub>1</sub></em>) (<em>b<sub>2</sub>,s<sub>2</sub>,r<sub>2</sub></em>) (<em>b<sub>3</sub>,s<sub>3</sub>,r<sub>3</sub></em>) (<em>b<sub>4</sub>,s<sub>4</sub>,r<sub>4</sub></em>)(<em>p<sub>n</sub>,q<sub>n</sub></em>) = (0,0,0) (23,0,0) (1,2,0) (0,0,0) ([5,8],2) and shows that air temperature on t-day affects rainfall on t-day, rainfall on t-day is influenced by air humidity in the previous 23 days, rainfall on t-day is affected by wind speed in the previous day , and rainfall on day t is affected by clouds on day t. The results of rainfall forecasting in Batu City with multi input transfer function model can be said to be accurate, because it produces relatively small RMSE value. The value of RMSE data forecasting training is 7.7921 while forecasting data testing is 4.2184. Multi-input transfer function model is suitable for rainfall in Batu City.


2019 ◽  
Vol 7 (3) ◽  
Author(s):  
Nur Laela Fitriani ◽  
Pika Silvianti ◽  
Rahma Anisa

Transfer function model with multiple input is a multivariate time series forecasting model that combines several characteristics of ARIMA models by utilizing some regression analysis properties. This model is used to determine the effect of output series towards input series so that the model can be used to analyze the factors that affect the Jakarta Islamic Index (JII). The USD exchange rate against rupiah and Dow Jones Index (DJI) were used as input series. The transfer function model was constructed through several stages: model identification stage, estimation of transfer function model, and model diagnostic test. Based on the transfer function model, the JII was influenced by JII at the period of one and two days before. JII was also affected by the USD exchange rate against rupiah at the same period and at one and two days before. In addition, the JII was influenced by DJI at the same period and also at period of one until five days ago. The Mean Absolute Prencentage Error (MAPE) value of forecasting result was 0.70% and the correlation between actual and forecast data was 0.77. This shows that the model was well performed for forecasting JII.


Economies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 21
Author(s):  
Jazmín González Aguirre ◽  
Alberto Del Villar

This paper seeks to assess the effectiveness of customs policies in increasing the resources devoted to controlling and inspection. Specifically, it seeks to analyze whether an increase in the administrative cost of collecting taxes on foreign trade in Ecuador contributes to reducing customs fraud. To this end, we identify and estimate a transfer function model (ARIMAX), considering information on foreign trade such as official international trade statistics report and tariff rates, as well as the execution of budgetary expenditure and Ecuador’s gross domestic product (GDP). The period under study includes quarterly series from 2006 to 2018. The results obtained by the model indicate that allocating greater material and budgetary resources to combat customs fraud does not always achieve the objective of reducing customs evasion.


Sign in / Sign up

Export Citation Format

Share Document