A Forecasting Method for Fertilizers Consumption in Brazil

2013 ◽  
Vol 4 (2) ◽  
pp. 23-36 ◽  
Author(s):  
Eduardo Ogasawara ◽  
Daniel de Oliveira ◽  
Fabio Paschoal Junior ◽  
Rafael Castaneda ◽  
Myrna Amorim ◽  
...  
Keyword(s):  
Large Scale ◽  
Moving Average ◽  
Logistic Function ◽  
Autoregressive Integrated Moving Average ◽  
Forecasting Method ◽  
The World ◽  
Entire Country ◽  
Function Models ◽  
Nitrogen Phosphorus

Tracking information about fertilizers consumption in the world is very important since they are used to produce agriculture commodities. Brazil consumes a large amount of fertilizers due to its large-scale agriculture fields. Most of these fertilizers are currently imported. The analysis of consumption of major fertilizers, such as Nitrogen-Phosphorus-Potassium (NPK), Sulfur, Phosphate Rock, Potash, and Nitrogen become critical for long-term government decisions. In this paper we present a method for fertilizers consumption forecasting based on both Autoregressive Integrated Moving Average (ARIMA) and logistic function models. Our method was used to forecast fertilizers consumption in Brazil for the next 20 years considering different economic growth for the entire country.

scholarly journals Implications of the COVID-19 Lockdown on Dengue Transmission in Malaysia

2021 ◽  
Vol 13 (1) ◽  
pp. 148-160
Author(s):  
Song-Quan Ong ◽  
Hamdan Ahmad ◽  
Ahmad Mohiddin Mohd Ngesom
Keyword(s):  
Large Scale ◽  
Moving Average ◽  
Human Movement ◽  
Population Movement ◽  
Sarima Model ◽  
Autoregressive Integrated Moving Average ◽  
Predominant Species ◽  
Lower Confidence ◽  
Dengue Transmission ◽  
Stage 1

We aim to investigate the effect of large-scale human movement restrictions during the COVID-19 lockdown on both the dengue transmission and vector occurrences. This study compared the weekly dengue incidences during the period of lockdown to the previous years (2015 to 2019) and a Seasonal Autoregressive Integrated Moving Average (SARIMA) model that expected no movement restrictions. We found that the trend of dengue incidence during the first two weeks (stage 1) of lockdown decreased significantly with the incidences lower than the lower confidence level (LCL) of SARIMA. By comparing the magnitude of the gradient of decrease, the trend is 319% steeper than the trend observed in previous years and 650% steeper than the simulated model, indicating that the control of population movement did reduce dengue transmission. However, starting from stage 2 of lockdown, the dengue incidences demonstrated an elevation and earlier rebound by four weeks and grew with an exponential pattern. We revealed that Aedes albopictus is the predominant species and demonstrated a strong correlation with the locally reported dengue incidences, and therefore we proposed the possible diffusive effect of the vector that led to a higher acceleration of incidence rate.

scholarly journals A statistical study of COVID-19 pandemic in Egypt

2021 ◽  
Vol 54 (1) ◽  
pp. 233-244
Author(s):  
Taha Radwan
Keyword(s):  
Linear Relationship ◽  
Statistical Study ◽  
Moving Average ◽  
Arima Model ◽  
Decision Makers ◽  
Accurate Data ◽  
Autoregressive Integrated Moving Average ◽  
The World ◽  
The Future

Abstract The spread of the COVID-19 started in Wuhan on December 31, 2019, and a powerful outbreak of the disease occurred there. According to the latest data, more than 165 million cases of COVID-19 infection have been detected in the world (last update May 19, 2021). In this paper, we propose a statistical study of COVID-19 pandemic in Egypt. This study will help us to understand and study the evolution of this pandemic. Moreover, documenting of accurate data and taken policies in Egypt can help other countries to deal with this epidemic, and it will also be useful in the event that other similar viruses emerge in the future. We will apply a widely used model in order to predict the number of COVID-19 cases in the coming period, which is the autoregressive integrated moving average (ARIMA) model. This model depicts the present behaviour of variables through linear relationship with their past values. The expected results will enable us to provide appropriate advice to decision-makers in Egypt on how to deal with this epidemic.

scholarly journals Autoregressive Integrated Moving Average (ARIMA) Sebagai Model Peramalan Kasus Demam Berdarah Dengue

2020 ◽  
Vol 10 (2) ◽  
pp. 76-80
Author(s):  
Roro Kushartanti ◽  
Maulina Latifah
Keyword(s):  
Community Health ◽  
Health Center ◽  
Moving Average ◽  
Arima Model ◽  
Community Health Center ◽  
Percentage Error ◽  
Dengue Case ◽  
Monthly Data ◽  
Autoregressive Integrated Moving Average ◽  
Forecasting Method

ARIMA is a forecasting method time series that does not require a specific data pattern. This study aims to analyze the forecasting of Semarang City DHF cases specifically in the Rowosari Community Health Center. The study used monthly data on DHF cases in the Rowosari Community Health Center in 2016, 2017, and 2019 as many as 36 dengue case data. The best ARIMA model for forecasting is a model that meets the requirements for parameter significance, white noise and has the MAPE (Mean Absolute Percentage Error Smallest) value. The results of the analysis show that the best model for predicting the number of dengue cases in the Rowosari Public Health Center Semarang is the ARIMA model (1,0,0) with a MAPE value of 43.98% and a significance coefficient of 0.353, meaning that this model is suitable and feasible to be used as a forecasting model. DHF cases in the Rowosari Community Health Center in Semarang City.

scholarly journals Transfer Function Analysis: Modelling Residential Building Costs in New Zealand by Including the Influences of House Price and Work Volume

Buildings ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 152
Author(s):  
Linlin Zhao ◽  
Jasper Mbachu ◽  
Zhansheng Liu ◽  
Huirong Zhang
Keyword(s):  
Time Series ◽  
New Zealand ◽  
Transfer Function ◽  
Moving Average ◽  
Cost Data ◽  
Autoregressive Integrated Moving Average ◽  
Work Volume ◽  
Moving Average Models ◽  
Function Models ◽  
Transfer Function Models

An accurate cost estimate not only plays a key role in project feasibility studies but also in achieving a final successful outcome. Conventionally, estimating cost typically relies on the experience of professionals and cost data from previous projects. However, this process is complex and time-consuming, and it is challenging to ensure the accuracy of the estimates. In this study, the bivariate and multivariate transfer function models were adopted to estimate and forecast the building costs of two types of residential buildings in New Zealand: Low-rise buildings and high-rise buildings. The transfer function method takes advantage of the merits of univariate time series analysis and the power of explanatory variables. In the dynamic project conduction environment, simply including building cost data in the cost forecasting models is not valid for making predictions, because the change in demand must be considered. Thus, the time series of house prices and work volume were used to explain exogenous effects in the transfer function model. To demonstrate the effectiveness of transfer function models, this study compared the results generated by the transfer function models with autoregressive integrated moving average models. According to the forecasting performance of the models, the proposed approach achieved better results than autoregressive integrated moving average models. The proposed method can provide accurate cost estimates that can help stakeholders in project budget planning and management strategy making at the early stage of a project.

Contrasting tactical and strategic dynamics on a Clausewitz landscape

2019 ◽  
Vol 17 (2) ◽  
pp. 143-153
Author(s):  
Rodrick Wallace
Keyword(s):  
Statistical Models ◽  
Limit Theorems ◽  
Large Scale ◽  
Evolutionary Process ◽  
Short Term ◽  
Local Resources ◽  
Human Organization ◽  
The World ◽  
Short Time

Statistical models based on the asymptotic limit theorems of control and information theories allow formal examination of the essential differences between short-time “tactical” confrontations and a long-term “strategic” conflict dominated by evolutionary process. The world of extended coevolutionary conflict is not the world of sequential “muddling through.” The existential strategic challenge is to take cognitive control of a long-term dynamic in which one may, in fact, be “losing” most short-term confrontations. Winning individual battles can be a relatively direct, if not simple or easy, matter of sufficient local resources, training, and resolve. Winning extended conflicts is not direct, and requires management of subtle coevolutionary phenomena subject to a dismaying punctuated equilibrium more familiar from evolutionary theory than military doctrine. Directed evolution has given us the agricultural base needed for large-scale human organization. Directed coevolution of the inevitable conflicts between the various segments of that organization may be needed for its long-term persistence.

scholarly journals Detection of Tea Export Potentiality from Bangladesh in the World Market: An Autoregressive Integrated Moving Average (ARIMA) Approach

2020 ◽  
pp. 21-29
Author(s):  
A. U. Noman ◽  
S. Majumder ◽  
M. F. Imam ◽  
M. J. Hossain ◽  
F. Elahi ◽  
...  
Keyword(s):  
Mean Absolute Error ◽  
Moving Average ◽  
Arima Model ◽  
Absolute Error ◽  
World Market ◽  
Information Criteria ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Autoregressive Integrated Moving Average ◽  
The World

Export plays an important role in promoting economic growth and development. The study is conducted to make an efficient forecasting of tea export from Bangladesh for mitigating the risk of export in the world market. Forecasting has been done by fitting Box-Jenkins type autoregressive integrated moving average (ARIMA) model. The best ARIMA model is selected by comparing the criteria- coefficient of determination (R2), root mean square error (RMSE), mean absolute percentage error (MAPE), mean absolute error (MAE) and Bayesian information criteria (BIC). Among the Box-Jenkins ARIMA type models for tea export the ARIMA (1,1,3) model is the most appropriate one for forecasting and the forecast values in thousand kilogram for the year 2017-18, 2018-19, 2019-20, 2020-21 and 2021-22, are 1096.48, 812.83, 1122.02, 776.25 and 794.33 with upper limit 1819.70, 1348.96, 1862.09, 1288.25, 1318.26 and lower limit 660.69, 489.78, 676.08, 467.74, 478.63, respectively. So, the result of this model may be helpful for the policymaker to make an export development plan for the country.

scholarly journals YOUTH EMPLOYMENT AND UNEMPLOYMENT UNDER THE INFLUENCE OF THE COVID-19 PANDEMIC

2020 ◽  
pp. 69-74
Author(s):  
Oxana Martirosyan ◽  
Keyword(s):  
Large Scale ◽  
Well Being ◽  
Quality Education ◽  
International Labour Organization ◽  
Decent Work ◽  
Youth Labor Market ◽  
The World ◽  
Long Term Consequences ◽  
Mental Well Being

The economic crisis caused by the spread of the COVID-19 pandemic has led to serious long-term consequences for young people around the world, primarily because States have suspended funding for education and a large number of youth projects, and many children and adolescents have not been able to implement their plans for quality education and decent work. The international labour organization conducted a large-scale study on “Youth and COVID-19: impact on jobs, education, rights and mental well-being”, covering 112 countries and 120 thousand respondents. The article presents some results of this study, reflecting the situation in the youth labor market.

scholarly journals Practice of Preserving Collections in the Library and Archives Canada

2020 ◽  
Vol 69 (5) ◽  
pp. 509-521
Author(s):  
Ekaterina A. Barysheva
Keyword(s):  
Large Scale ◽  
Storage Conditions ◽  
Government Support ◽  
Storage Facility ◽  
Federal Department ◽  
The World ◽  
Library And Archives Canada ◽  
Storage Facilities ◽  
Library Collections

The Library and Archives of Canada (LAC) is Federal department of Canada established by the Parliament of Canada in 2004 to integrate services and functions of the National library and the National Archives of Canada; and currently it is the fourth-largest library in the world. The article discusses the experience of the Library and Archives Canada in creating modern centres for preserving documentary heritage, organizing the work of collections management, their conservation and restoration, ensuring openness and accessibility of collections. The main sources were materials published on the LAC website, primarily planning, reporting and financial documentation of the institution, as well as publications in the Canadian periodical press. Special attention is paid to the buildings and premises of the LAC storage facilities. The author describes the concept of the project of the Gatineau Preservation Centre, GPC. The complex, opened in 1997, is one of the top architectural objects constructed in Canada in the 20th century and one of the most secure library storage facilities in the world. The article considers organization of collections storage in the GPC and the work of restoration laboratories located in it. The author shows that GPC provides the most favourable storage conditions for the most valuable and vulnerable LAC collections. The paper gives information about the storage facility in the main LAC building in Ottawa on Wellington Street (built in 1967; modernized in the early 2000s), as well as storage facilities in Gatineau, Renfrew and Winnipeg.The author characterizes the new version of the LAC Collections Preservation Program (2018) which defines the strategic objectives of the institution in this area, both for the nearest future and for the long term. The paper presents results of a large-scale study of the state of the collections storage in LAC (2016—2018) and outlines the most acute problems identified in this study. There is emphasized the importance of the construction of the new Gatineau-2 complex, launched in 2019 (Project cost is 330 million Canadian dollars). According to experts, Gatineau-2 will become one of the largest, technologically equipped and environmental centres for the conservation and restoration of library collections in the world, as well as the first zero-energy storage facility in North America. In Canada, special attention is paid to the construction of modern centres for the preservation of documentary heritage, which create all the necessary conditions for long-term security of collections, conservation and restoration work. Implementation of such projects is impossible without government support, without understanding by authorities of the leading role of libraries and archives in the preservation and promotion of the national cultural heritage. The experience of LAC may be of interest to Russia, taking into account the tasks set in the document “The main directions of development of activities to preserve library collections in the Russian Federation for 2011—2020” and elaboration of long-term programs in this area.

scholarly journals An ARIMA Model to Forecast the Spread and the Final Size of COVID-2019 Epidemic in Italy

2020 ◽  
Author(s):  
Gaetano Perone
Keyword(s):  
Inflection Point ◽  
Social Impact ◽  
Moving Average ◽  
Arima Model ◽  
Epidemiological Data ◽  
List Type ◽  
Arima Models ◽  
Final Size ◽  
Autoregressive Integrated Moving Average ◽  
The World

AbstractCoronavirus disease (COVID-2019) is a severe ongoing novel pandemic that is spreading quickly across the world. Italy, that is widely considered one of the main epicenters of the pandemic, has registered the highest COVID-2019 death rates and death toll in the world, to the present day. In this article I estimate an autoregressive integrated moving average (ARIMA) model to forecast the epidemic trend over the period after April 4, 2020, by using the Italian epidemiological data at national and regional level. The data refer to the number of daily confirmed cases officially registered by the Italian Ministry of Health (www.salute.gov.it) for the period February 20 to April 4, 2020. The main advantage of this model is that it is easy to manage and fit. Moreover, it may give a first understanding of the basic trends, by suggesting the hypothetic epidemic’s inflection point and final size.Highlights❖ARIMA models allow in an easy way to investigate COVID-2019 trends, which are nowadays of huge economic and social impact.❖These data may be used by the health authority to continuously monitor the epidemic and to better allocate the available resources.❖The results suggest that the epidemic spread inflection point, in term of cumulative cases, will be reached at the end of May.❖Further useful and more precise forecasting may be provided by updating these data or applying the model to other regions and countries.

scholarly journals Real-Time Forecasting of COVID-19 prevalence in India using ARIMA Model

2020 ◽  
Vol 4 (10) ◽  
pp. 78-83
Keyword(s):  
Time Series ◽  
Virus Disease ◽  
Moving Average ◽  
Time Series Prediction ◽  
Arima Model ◽  
Autoregressive Integrated Moving Average ◽  
Daily Data ◽  
The World ◽  
Increasing Trend ◽  
Short Term Prediction

Corona virus disease (COVID -19) has changed the world completely due to unavailability of its exact treatment. It has affected 215 countries in the world in which India is no exception where COVID patients are increasing exponentially since 15th of Feb. The objective of paper is to develop a model which can predict daily new cases in India. The autoregressive integrated moving average (ARIMA) models have been used for time series prediction. The daily data of new COVID-19 cases act as an exogenous variable in this framework. The daily data cover the sample period of 15th February, 2020 to 24th May, 2020. The time variable under study is a non-stationary series as 𝒚𝒕 is regressed with 𝒚𝒕−𝟏 and the coefficient is 1. The time series have clearly increasing trend. Results obtained revealed that the ARIMA model has a strong potential for short-term prediction. In PACF graph. Lag 1 and Lag 13 is significant. Regressed values implies Lag 1 and Lag 13 is significant in predicting the current values. The model predicted maximum COVID-19 cases in India at around 8000 during 5thJune to 20th June period. As per the model, the number of new cases shall start decreasing after 20th June in India only. The results will help governments to make necessary arrangements as per the estimated cases. The limitation of this model is that it is unable to predict jerks on either lower or upper side of daily new cases. So, in case of jerks re-estimation will be required.

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