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.