Cost Prediction
A Fuzzy/Neural Approach to Cost Prediction with Small Data Sets
... Accurate Cost Estimating Model is a system using several Adaptive Network-Based Fuzzy Inference Systems (ANFIS) developed to predict the cost of engine and component tests for the testing facilities of ...
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Towards virtual machine energy-aware cost prediction in clouds
... increasing cost of electricity, Cloud providers consider power consumption as one of the major cost factors to be maintained within their ...potential cost of resource usage and power consumption has ...
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Developing Cost Prediction Model for Building Project : Conclusion
... at cost much higher than estimated project cost, hence it is essential to develop a cost prediction model that imprison all factors affecting the project cost using regression analysis ...
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Bitcoin Cost Prediction using Deep Neural Network Technique
... price prediction, the impact of cryptocurrency in real ...long-term prediction of the exchange price in crypto-currencies particularly in US dollar, based on historical ...bitcoin cost ...
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Bridge Construction Cost Prediction using Multiple Linear Regression
... Abstract: Cost of construction of bridges is predicted using multiple linear regression model, based on data of bridges from Maharashtra state in ...India. Cost per unit area is taken as an appropriate ...
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Looking at Comparisons of Regression and Analogy-based Software Project Cost Prediction
... Project cost prediction is an important and problematic element to successful software engineering. Despite being a research topic for over forty years, a general solution remains elusive. There exists a ...
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An Analysis of Data Sets Used to Train and Validate Cost Prediction Systems
... Additional information was also collected since this pilot is in fact part of a larger study to conduct a meta-analysis of all empirical cost prediction results, however, this is beyond the scope of this ...
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Material Cost Prediction for Jewelry Production Using Deep Learning Technique
... On the contrary, the investors in the future exchange market generally use traditional time-series forecasting models that can be customized and fine-tuned, such models are too complicated and too much time consuming to ...
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Office building maintenance: Cost prediction model
... and cost performance were analysed to obtain information for the prediction of maintenance ...The prediction of the value of a dependent variable from the value of an independent variable is called ...
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Research on Investment Forecast of Substation Project Based on Neural Network Model
... intelligent cost prediction model, supported by the final account data of historical power transmission and transformation projects, the model is trained for reinforcement learning; and by inputting the key ...
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Estimating the economic life of forest machinery using the cumulative cost model and cost minimization model in Iranian Caspian forests
... operating cost model for HSM 904 that corresponded with the models developed by Karimi et ...better cost prediction with higher confidence and less variation than the other models because of easiness ...
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Malaria and protective behaviours: is there a malaria trap?
... economic cost of protection and (c) decrease with an increase of the incidence of extreme ...poverty. Prediction (a) is testable with existing individual data as examined ...1. Prediction (b) is ...
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Prediction of health care expenditure increase: how does pharmacotherapy contribute?
... BDT prediction is generated during the inference ...decrease prediction, respectively. The final prediction is an in- crease, if the sum of all scores is positive; otherwise it is a ...
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Low-cost scalable discretization, prediction, and feature selection for complex systems
... the cost scaling that grows polynomial with the dimension and the size of the statistics, rendering some form of ad hoc preprocessing and prereduction with more simple approaches ...lower cost of the method ...
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No prediction error cost in reading : evidence from eye movements
... In general, we believe that the present results are best accommodated by a model in which predictability effects arise by means of pre-activation of multiple lexical items, roughly in proportion to their predictability ...
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House Hold Price Statistical Analysis through Linear Regression
... any prediction model we need to understand whether there is any underlying relationship between the variables which are being ...the prediction model accuracy can be ...
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Efficient Cost Estimation Techniques for Web Applications
... Web cost estimation proposes models based on late product size measures, such as number of HTML pages, number of images ...of cost-benefit ...different cost predictors are, and if there are any ...
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Consideration of Uneven Misclassification Cost and Group Size for Bankruptcy Prediction
... misclassification cost and group size. Uneven cost of misclassification results from Type I (misclassify a healthy company as a failure) and Type II errors (misclassify a failed company as healthy), which ...
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An implementation of effective stock analysis and prediction system
... Output of proposed system is user friendly, web browser providing various tabs for different category of stocks analysis like stocks in uptrend, downtrend, price gainers and losers, overbought and oversold stocks, stock ...
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Cost and Time Effective Prediction of Soil Characteristics using ANN Model
... capacity for any input values. The advantage of using the Artificial Neural Network comes mainly from saving calculation time of the parameters and the ultimate bearing capacity, and once the network was ready, the same ...
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