Rate-Distortion Cost Estimation Model Based on Cauchy Distributions for HEVC Encoder

Author(s):  
Yanling Xu ◽  
Yueqiang Lin ◽  
Chenfeng Yu
2012 ◽  
Vol 490-495 ◽  
pp. 2173-2177
Author(s):  
Bin Zeng ◽  
Rui Wang ◽  
Chao Yang Ma

Traditionally assembly cost models are established through static spreadsheet algorithms. However, there are some inherent problems in using spreadsheets for the estimation of manufacturing cost. Among these is the lack of accounting for dynamic effects caused by stochastic variation such as inventory fluctuation, downtimes, supply interruptions, and system failures. Therefore, a dynamic cost estimation model is proposed which can be seen as an integration method between spreadsheet modeling and the virtual plant concept, which maintained the accessibility and flexibility of the spreadsheet model, and did not require a significant increase in the effort level to build a simulation. However, it still includes the effects of interaction between machines, along with simulating random failures, maintenance dispatch and repair. A case study is also tested and the results verify that the methodology demonstrates the feasibility of dynamic cost model based on a number of improvements on static spreadsheet algorithms


2013 ◽  
Vol 671-674 ◽  
pp. 3100-3106
Author(s):  
Xin Liang Liu ◽  
Tao Yin ◽  
Guo Dong Wu

Early understanding of construction cost represents a critical factor of a feasibility study in the early design phase of a project. A new project cost estimation model based on Gaussian Process was proposed. Gaussian Process model theory was introduced, and project cost estimation model based on Gaussian Process’ flow chart was analyzed in detail. Through example analysis, project cost estimation model based on Gaussian Process using Nelder-Mead and genetic algorithms algorithm was proven feasible for this problem and represented accuracy than BP neural network.


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