Forecasting Models/ Time Series
davood darvishi; Mostafa Nori joybari; parvin babaei
Abstract
Purpose: Covid-19 virus is a major threat to the health and safety of people around the world. One of the key components in dealing with this global threat is rapid and timely decision-making to control the epidemic of the disease, so predicting the future trend of this disease in the world, including ...
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Purpose: Covid-19 virus is a major threat to the health and safety of people around the world. One of the key components in dealing with this global threat is rapid and timely decision-making to control the epidemic of the disease, so predicting the future trend of this disease in the world, including predicting deaths, can be useful for policy-making, management and control of its prevalence. Therefore, the mortality rate caused by this virus has been predicted with grey models in the world.Methodology: This study examines the process of predicting mortality rates in the world using the theory of grey systems models. Research data were collected from the World Health Organization website and predicted the number of deaths in the world on a monthly basis by five methods: GM (1, 1), Verhulst Grey, DGM (1, 1), NGBM (1, 1) and FNGBM(1, 1). In order to evaluate the error of the models, the common error evaluation criteria MAE, RMSE and MAPE were used.Findings: By evaluating the model error, the prediction of the F-NGBM model (1, 1) in the category of excellent models, the prediction values of the GreyVerhulst model are in the category of acceptable predictions and the rest of the models are in the category of good predictions. Also, the F-NGBM (1, 1) model with MAE, RMSE and MAPE error values of 26989.54, 21533.94 and 7.21, respectively, is the most suitable model compared to the other methods. An estimated 250,958 deaths are estimated by the F-NGBM (1.1) model by the end of 2021, which may be the most appropriate value among forecasting methods.Originality/Value: Due to the lack of historical data and also a lot of uncertainty in the available data, it is necessary to use approaches to dealing with uncertainty such as the grey system theory in predicting the mortality rate of this disease. Various grey predictions estimate the mortality rate, which requires relatively less data than existing methods, and the model error is much lower. The study also looked at the worldwide mortality rate and will be more comprehensive on integrated global action.
Management and operational budgeting
Malihe Niksirat; Seyed Hadi Nasseri
Abstract
Corona is currently the world's health crisis and the biggest challenge humans have experienced since World War II. Given the epidemic of the disease, it is invaluable to forecasting the number of cases and the resulting deaths to better understand the current situation and provide a short-term plan ...
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Corona is currently the world's health crisis and the biggest challenge humans have experienced since World War II. Given the epidemic of the disease, it is invaluable to forecasting the number of cases and the resulting deaths to better understand the current situation and provide a short-term plan by managers. Accordingly, in this paper, a neuro-fuzzy network model is proposed to forecast the number of cases and deaths in countries that are most affected by this disease. The performance of the proposed neuro-fuzzy network has been compared with time series forecasting neural network as well as radial basic functions neural networks. The proposed model is able to predict the number of cases and deaths from the disease for a period of the next 15 days at a lower error rate.
Forecasting Models/ Time Series
Moeen Sammak Jalali; Seyed Mohammad Taghi Fatemi Ghomi
Abstract
Among various applications of time series, applying this concept in production industries with the intention of pre-detecting failure times of machines and implementing maintenance tasks, is considered as one of the most valuable activities in the automotive industries. With this regard, this article ...
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Among various applications of time series, applying this concept in production industries with the intention of pre-detecting failure times of machines and implementing maintenance tasks, is considered as one of the most valuable activities in the automotive industries. With this regard, this article embarks on applying time series analysis as well as quality assurance concepts to detect failure times and implement proper actions. With this regard, we will analyze the data derived from maintenance department of the company. Then we determine influential factors on parts failure by means of quality assurance concepts.