PRINCIPLE: The UVE algorithm detects and eliminates from a PLS model (including from 1 to A components) those variables that do not carry any relevant information to model Y. The criterion used to trace the un-informative variables is the reliability of the regression coefficients: c_j=mean(b_j)/std(b_j), obtained by jackknifing. The cutoff level, below which c_j is considered to be too small, indicating that the variable j should be removed, is estimated using a matrix of random variables.The Predictive power of PLS models built on the retained variables only is evaluated over all 1-a dimensions =(yielding RMSECVnew).
標簽： from eliminates PRINCIPLE algorithm
上傳時間： 2016-11-27
上傳用戶：凌云御清風
Computational models are commonly used in engineering design and scientific discovery activities for simulating complex physical systems in disciplines such as fluid mechanics, structural dynamics, heat transfer, nonlinear structural mechanics, shock physics, and many others. These simulators can be an enormous aid to engineers who want to develop an understanding and/or Predictive capability for complex behaviors typically observed in the corresponding physical systems. Simulators often serve as virtual prototypes, where a set of predefined system parameters, such as size or location dimensions and material properties, are adjusted to improve the performance of a system, as defined by one or more system performance objectives. Such optimization or tuning of the virtual prototype requires executing the simulator, evaluating performance objective(s), and adjusting the system parameters in an iterative, automated, and directed way. System performance objectives can be formulated, for example, to minimize weight, cost, or defects; to limit a critical temperature, stress, or vibration response; or to maximize performance, reliability, throughput, agility, or design robustness. In addition, one would often like to design computer experiments, run parameter studies, or perform uncertainty quantification (UQ). These approaches reveal how system performance changes as a design or uncertain input variable changes. Sampling methods are often used in uncertainty quantification to calculate a distribution on system performance measures, and to understand which uncertain inputs contribute most to the variance of the outputs. A primary goal for Dakota development is to provide engineers and other disciplinary scientists with a systematic and rapid means to obtain improved or optimal designs or understand sensitivity or uncertainty using simulationbased models. These capabilities generally lead to improved designs and system performance in earlier design stages, alleviating dependence on physical prototypes and testing, shortening design cycles, and reducing product development costs. In addition to providing this practical environment for answering system performance questions, the Dakota toolkit provides an extensible platform for the research and rapid prototyping of customized methods and meta-algorithms
標簽： Optimization and Uncertainty Quantification
上傳時間： 2016-04-08
上傳用戶：huhu123456
High-speed Precision Numerically Controlled Tapping Using Dual Predictive Control
標簽： 神經網絡控制
上傳時間： 2016-07-20
上傳用戶：ss183968ss
滑模預測控制的一片很好的文獻，內容詳細，對學習滑模預測控制的很有幫助。
標簽： Predictive Discrete Control Sliding Mode
上傳時間： 2017-08-05
上傳用戶：zhangyu97284
Unlock deeper insights into machine learning with this vital guide to cutting-edge Predictive analytics
上傳時間： 2017-10-27
上傳用戶：shawnleaves
The 4.0 kbit/s speech codec described in this paper is based on a Frequency Domain Interpolative (FDI) coding technique, which belongs to the class of prototype waveform Interpolation (PWI) coding techniques. The codec also has an integrated voice activity detector (VAD) and a noise reduction capability. The input signal is subjected to LPC analysis and the prediction residual is separated into a slowly evolving waveform (SEW) and a rapidly evolving waveform (REW) components. The SEW magnitude component is quantized using a hierarchical Predictive vector quantization approach. The REW magnitude is quantized using a gain and a sub-band based shape. SEW and REW phases are derived at the decoder using a phase model, based on a transmitted measure of voice periodicity. The spectral (LSP) parameters are quantized using a combination of scalar and vector quantizers. The 4.0 kbits/s coder has an algorithmic delay of 60 ms and an estimated floating point complexity of 21.5 MIPS. The performance of this coder has been evaluated using in-house MOS tests under various conditions such as background noise. channel errors, self-tandem. and DTX mode of operation, and has been shown to be statistically equivalent to ITU-T (3.729 8 kbps codec across all conditions tested.
標簽： frequency-domain interpolation performance Design kbit_s speech coder based and of
上傳時間： 2018-04-08
上傳用戶：kilohorse
I saw the light of the future when I first read Ray Kurzweil’s best-seller book The Singularity Is Near: When Humans Transcend Biology. One cubic inch of nanotube cir- cuitry, once fully developed, would be up to one hundred million times more powerful than the human brain.
標簽： Predictive Cognitive Warning System Early The
上傳時間： 2020-05-26
上傳用戶：shancjb
The continuous progress in modern power device technology is increasingly supported by power-specific modeling methodologies and dedicated simulation tools. These enable the detailed analysis of operational principles on the the device and on the system level; in particular, they allow the designer to perform trade- off studies by investigating the operation of competing design variants in a very early stage of the development process. Furthermore, using Predictive computer simulation makes it possible to analyze the device and system behavior not only under regularoperatingconditions, but also at the rim of the safe-operatingarea and beyond of it, where destructive processes occur that limit the lifetime of a power system.
標簽： POWERHVMOS_Devices_Compact_Modeli ng
上傳時間： 2020-06-07
上傳用戶：shancjb
這是一本英文版的MPC的MATLAB教程，講這一塊的資料太少了，故上傳一本。MPC is one of the few areas that has received on-going interest from researchers in both the industrial and cademic communities.Four major aspects of model Predictive control make the design methodology attractive to both practitioners and academics.This is particularly attractive to industry where tight profit margins and limits on the process operation are inevitably present. The third aspect is the ability to perform on-line process optimization. The fourth aspect is the simplicity of the design framework in handling all these complex issues.
標簽： 模型預測控制
上傳時間： 2022-05-05
上傳用戶：zhanglei193
很難下載到的預測控制書籍資源，5分拿去把。Rawlings是預測控制界的大牛，懂的人自然都懂。
標簽： 模型預測控制
上傳時間： 2022-07-05
上傳用戶：
