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.
Management and operational budgeting
Reza Bandarian
Abstract
The deviation between the raw estimation of size, time, and cost of projects and the real amount of them after execution projects, will lead to several difficulties for contractors. This fact demonstrates an essential to apply scientific methods to increase the accuracy of the early estimations. There ...
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The deviation between the raw estimation of size, time, and cost of projects and the real amount of them after execution projects, will lead to several difficulties for contractors. This fact demonstrates an essential to apply scientific methods to increase the accuracy of the early estimations. There are several approaches to calculate the cost of projects and one of them is algorithmic modeling. This study developed an algorithmic cost model to estimate size, time, and cost of engineering services project by benchmarking from Constructive Cost Model (COCOMO), which is an empirical model for calculating the cost of the software. This model uses size and cost drivers to increase the accuracy of estimation. The developed model has been run for a case study and by historical data from previous projects validated.