نتایج جستجو برای: cost and time estimation
تعداد نتایج: 17086956 فیلتر نتایج به سال:
Now a day’s software cost/effort estimation is a very complex job to do. Several estimation techniques have been developed in this regard. This assessment of parameters like, time, cost, and number of staff required sequentially which in turn is to be done at an early stage. Constructive Cost model which is also known as COCOMO model was one of the best model to estimate the cost and time in pe...
With regard to importance of investment as an engine of economic growth many economists such as Wicksel, Keynse and Harrod believe that investment is the main source of business cycles. Hence this study specifies investment function according to a basic macroeconomic model such as Ramsey model. Application of Ramsey model can help to extend macroeconomics with micro foundations in economy of I...
There is a growing recognition that discrete choice models are capable of providing a more realistic picture of route choice behavior. In particular, influential factors other than travel time that are found to affect the choice of route trigger the application of random utility models in the route choice literature. This paper focuses on path-based, logit-type stochastic route choice models, i...
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O-Anisidines (OAs) are extensively used as an intermediate for chemical reactions to produce various triphenylmethane and azo dyes, and also in manufacturing numerous pigments. They are found to be highly toxic and have carcinogenic properties, so it is imperative to treat OA solutions before disposal. In this study a promising approach to degrade OA solutions has been carried out using Fenton’...
estimating of forest equipment productivity is an important aspect of managing cost in forestry, which leads to reduction of operations expenses. in other words, high capital cost in forest harvesting, is a good reason to argue forest engineering research and time modeling. this paper applied one of the artificial intelligence subsets, which are called artificial neural networks (anns), to pred...
| Modeling a noisy time series requires the dual estimation of both the model parameters and the underlying clean time series. Most approaches estimate the model parameters by minimizing the mean squared prediction error, but estimate the time series by minimizing another cost function. We justify the use of the same maximum-likelihood cost for both parameter and time series estimation, and pre...
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