OXIDATION RATE PREDICTION OF MO-SI-B ALLOY USING MACHINE LEARNING WITH RANDOM FOREST REGRESSOR METHOD

OXIDATION RATE PREDICTION OF MO-SI-B ALLOY USING MACHINE LEARNING WITH RANDOM FOREST REGRESSOR METHOD

Mo-Si-B alloy is a high-temperature material that can be one of the candidates for the constituent material of turbine jet engines because of its good oxidation resistance. Research related to the high-temperature oxidation behavior of Mo-Si-B alloys has been carried out experimentally which require...

Saved in:

書目詳細資料
主要作者:	Yuliasari, Adisya
格式:	Final Project
語言:	Indonesia
在線閱讀:	https://digilib.itb.ac.id/gdl/view/67913
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Institut Teknologi Bandung
語言:	Indonesia

相似書籍

Adjustment with many regressors under covariate-adaptive randomizations
由: JIANG, Liang, et al.
出版: (2023)

Preparation and enhanced oxidation behavior of microalloyed Mo₅SiB₂ alloy at 1300 °C
由: Zhang, Chenyang, et al.
出版: (2023)

CORROSION RATE PREDICTION OF MAGNESIUM ALLOY USING MACHINE LEARNING
由: Fitriani Jilan, Ayunisa

Mechanism of mechanical crystallization of amorphous Fe-Mo-Si-B alloy
由: Yao, B., et al.
出版: (2014)

Robust inference with stochastic local unit root regressors in predictive regressions
由: LIU, Yanbo, et al.
出版: (2023)

Lithium-ion battery remaining useful life prediction based on random forest machine learning
由: Li, Xinwei
出版: (2025)

Structural changes in heterogeneous panels with endogenous regressors
由: Baltagi, Badi H., et al.
出版: (2021)

Regression with Slowly Varying Regressors and Nonlinear Trends
由: PHILLIPS, Peter C. B.
出版: (2007)

Additive nonparametric regression in the presence of endogenous regressors
由: OZABACI, Deniz, et al.
出版: (2014)

Inference in continuous systems with mildly explosive regressors
由: CHEN, Ye, et al.
出版: (2017)

Inference in continuous systems with mildly explosive regressors
由: CHEN, Ye, et al.
出版: (2017)

Testing linearity using power transforms of regressors
由: BAEK, Yae In, et al.
出版: (2015)

CORROSION RATE PREDICTION OF HIGH ENTROPY ALLOY ALCOCRFENI IN NACL SOLUTION USING MACHINE LEARNING
由: Yulianto, Dwi

WEIBULL PARAMETER ESTIMATION USING MACHINE LEARNING WITH RANDOM FOREST METHOD
由: Risya, Prima

Travel time prediction using random forest
由: Pranesh, Chaitra
出版: (2019)

PREDICTING CUSTOMERS LOYALTY USING RANDOM FOREST
由: Belva, Ahmad

AIRBNB SINGAPORE LISTING PRICE PREDICTION USING MACHINE LEARNING TECHNIQUES: MULTIPLE LINEAR REGRESSION, RANDOM FOREST, AND GRADIENT BOOSTING
由: Hasanah, Siti

Clothing Extremity Identification Using Convolutional Neural Network Regressor
由: Ngo, Genevieve C, et al.
出版: (2018)

Robust econometric inference with mixed integrated and mildly explosive regressors
由: Peter C. B. PHILLIPS,, et al.
出版: (2016)

Limit Theory for Continuous Time Systems with Mildly Explosive Regressors
由: PHILLIPS, Peter C. B., et al.
出版: (2015)

Simultaneous Equations in Ordered Discrete Responses with Regressor-Dependent Thresholds
由: Lee, Myoung-jae, et al.
出版: (2005)

Online brain imaging by QR factorization of normalized regressor functions
由: Aqil, M., et al.
出版: (2014)

An exclusive regressors binary mixture model with an application to labour supply
由: Lu, Z.-H., et al.
出版: (2016)

Predicting Forest Fire Using Remote Sensing Data And Machine Learning
由: Yang, Suwei, et al.
出版: (2021)

Meta random forest : random forest with simple random forest as base model
由: Kurniawan, Billy
出版: (2020)

Predicting metabolic syndrome using the random forest method
由: Apilak Worachartcheewan, et al.
出版: (2018)

Foreign exchange prediction and trading using random forests
由: Tong, Xiaoshan
出版: (2019)

Predicting Metabolic Syndrome Using the Random Forest Method
由: Apilak Worachartcheewan, et al.
出版: (2015)

Nonparametric Structural Estimation via Continuous Location Shifts in an Endogenous Regressor
由: PHILLIPS, Peter C. B., et al.
出版: (2009)

Sequentially testing polynomial model hypotheses using power transforms of regressors
由: CHO, Jin Seo, et al.
出版: (2018)

Limit Theory for Cointegrated Systems with Moderately Integrated and Moderately Explosive Regressors
由: Magdalinos, Tassos, et al.
出版: (2009)

FOREST FIRE PREDICTION MODELING APPROACH BASED ON DETERMINATION OF FIRE SPOT DISTANCE THROUGH TEMPERATURE RATE USING MACHINE LEARNING AND MULTILATERATIONI
由: Amaliyah, Shafira

COMBINED METHOD OF LSTM AND RANDOM FOREST FOR TRAFFIC JAM PREDICTION
由: Arfina, Ayuni

Exchange rate prediction based on machine learning methods
由: Hong, Yuyue
出版: (2017)

ANALYSIS OF CASHLESS SOCIETY STATUS OF A COUNTRY BY USING THE RANDOM FOREST CLASSIFIER METHOD ON MACHINE LEARNING
由: Zahrotun Nihayah, Fajris

COMPARISON OF USE OF RANDOM FOREST ALGORITHM AND SUPPORT VECTOR MACHINE FOR GENDER CLASSIFICATION
由: Ashabul Kahfi, Muhammad

Predicting earthquake magnitude error with regression, decision tree & random forest
由: Antony, Tommy
出版: (2020)

Applying random forest and neural network model to predict customers' behaviors
由: Nguyen, Huong Ly
出版: (2020)

Synthesis of cobalt doped b-FeSi2 by mechanical alloying
由: Jamreonta Parinyataramas
出版: (2014)

Synthesis of cobalt doped b-FeSi2 by mechanical alloying
由: Jamreonta Parinyataramas
出版: (2006)