Machine learningnuclear datacriticalityIn this work, we aim to show that machine learning algorithms are promising tools for the identification of nuclear data that contribute to increased errors in transport simulations. We demonstrate this through an application of a machine learning algorithm (Random ...
The paper is divided into multiple sections. In the following section, we provide a consistent basic concept and equation for VOI computation. Second, we propose a workflow of assessing VOI usingmachine learning methodsand, following this, we test the proposed methodology by implementing it in an ...
The present work illustrates the application of machine learning algorithms for prediction of sinter machine productivity. The sinter machine productivity has been correlated with the quality of materials used in sintering and also with process parameters of sinter machine. In earlier works, attempts ...
Quick and accurate medical diagnoses are crucial for the successful treatment of diseases. Using machine learning algorithms and based on laboratory blood test results, we have built two models to predict a haematologic disease. One predictive model used all the available blood test parameters and the...
These Machine Learning Applications will transform the world and make our lives easier. Check out few of the most important applications of Machine Learning.
Machine Learning (ML) Algorithms GRU-SVM Linear Regression Multilayer Perceptron Nearest Neighbor Softmax Regression L2-SVM Results All experiments in this study were conducted on a laptop computer with Intel Core(TM) i5-6300HQ CPU @ 2.30GHz x 4, 16GB of DDR3 RAM, and NVIDIA GeForce GTX 960...
Machine learning algorithms (regression methods) are listed: – Least Squares Monte Carlo Methods (LSM) , is a state-of-the-art dynamic programming approach used in financial engineering with real options initially proposed by ( Longstaff and Schwartz, 2001 ). ( Jafarizadeh and Bratvold, 2009 ...
Machine learning (ML) is a subset of Artificial Intelligence (AI) that involves the development of algorithms and statistical models enabling computers to perform tasks without explicit instructions. By utilizing patterns and inference derived from data, ML algorithms can improve their performance over ...
In this research work, performance and emission parameters of wheat germ oil (WGO) -hydrogen dual fuel was investigated experimentally and these parameters were predicted using different machine learning algorithms. Initially, hydrogen injection with 5%, 10% and 15% energy share were used as the dua...
Another characteristic of the FNN is that determination of the initial topology could be based on the problem's features. And hence, understanding the problem can help in developing the network structure. 2.1. Applications of machine learning algorithms in the petroleum industry Application of the ...