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RikiMilasinovic

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Education

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Thesis TEW

Elke Louwye

This paper advances the Domain Segmentation based on Uncertainty in the Surrogate (DSUS) framework which is a novel approach to characterize the uncertainty in surrogates. The leave-one-out cross-validation technique is adopted in the DSUS framework to measure local errors of a surrogate. A method is proposed in this paper to evaluate the performance of the leave-out-out cross-validation errors as local error measures. This method evaluates local errors by comparing: (i) the leave-one-out cross-validation error with (ii) the actual local error estimated within a local hypercube for each training point. The comparison results show that the leave-one-out cross-validation strategy can capture the local errors of a surrogate. The DSUS framework is then applied to key aspects of wind resource as- sessment and wind farm cost modeling. The uncertainties in the wind farm cost and the wind power potential are successfully characterized, which provides designers/users more confidence when using these models

DSUS_MAO_2012_Jie

MDO_Lab

κβαντομηχανική

eigianni

Evaluation question 4

amymontaguechs01

My Self+My Health,Food, and Drink, Sports and Games2+ป.2+104+dltvengp1+54en p...

Prachoom Rangkasikorn

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Prachoom Rangkasikorn

This paper develops a novel approach to characterize the uncertainty in the accuracy of surrogate models. This technique segregates the design domain based on the level of cross-validation errors; the overall framework is called Domain Segmentation based on Uncertainty in the Surrogate (DSUS). The estimated errors are classified into physically meaningful classes based on the user’s understanding of the system and/or the accuracy requirements for the concerned system analysis. In each class, the distribution of the cross-validation errors is estimated to represent the uncertainty in the surrogate. Support Vector Machine (SVM) is implemented to determine the boundaries between error classes, and to classify any new design (point) into a meaningful class. The DSUS framework is illustrated using two different surrogate modeling methods: (i) the Kriging method, and (ii) the Adaptive Hybrid Functions (AHF). We apply the DSUS framework to a series of standard problems and engineering problems. The results show that the DSUS framework can successfully classify the design domain and quantify the uncertainty (prediction errors) in surrogates. More than 90% of the test points could be accurately classified into its error class. In real life engineering design, where we use predictive models with different levels of fidelity, the knowledge of the level of error and uncertainty at any location inside the design space is uniquely helpful.

DSUS_SDM2012_Jie

MDO_Lab

Medición de la Opinión Pública

Lucia Paradiso

The Web Team Inside the Museum: SFMOMA Case Study

Dana Mitroff Silvers

چای‌ سبز هم مانند بقیه انواع چای‌ها دارای تین و کافئین و سایر مواد تحریک کننده بوده مصرف فراوان و روزمره آن می‌تواند تولید اعتیاد کرده و بران بدن مضر می‌ باشد. باید دانست که مصرف هر نوع محرکی از جمله کافئین و تئین که درقهوه و چای موجود هستند می‌تواند بر غدد آدرنال اثر گذاشته، انرژی حیاتی بدن را تحلیل برده، ایجاد انرژی کاذب در بدن کرده در کار اندامهای مختلف اختلال ایجاد کند. طپش قلب یکی از نشانه‌های بارز اختلال در کار اندامهاست که در نتیجه مصرف چای از جمله چای سبز ایجاد می‌شود.

مضرات چای , چای سبز و قهوه و تاثیر آنها بر غدد فوق کلیوی

Farid Kamali

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Thesis TEW

DSUS_MAO_2012_Jie

κβαντομηχανική

Evaluation question 4

My Self+My Health,Food, and Drink, Sports and Games2+ป.2+104+dltvengp1+54en p...

ใบความรู้ ทฤษฎีใหม่ ป.3+446+dltvsocp3+54soc p03f 06-4page

DSUS_SDM2012_Jie

Medición de la Opinión Pública

The Web Team Inside the Museum: SFMOMA Case Study

مضرات چای , چای سبز و قهوه و تاثیر آنها بر غدد فوق کلیوی

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1. RIKARD MILAŠINOVIĆ

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