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 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 ...
Machine learning algorithms (regression methods) are listed: The mathematical depiction of the ordinary least square is the following:(5)yn=∑i=0kβixni+ϵwhere xi is the explanatory variable i.e. production profiles, and y is a dependent variable i.e. NPVs. The coefficient β minimizes ...
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...
We reviewed 16 studies that used ML approaches for irrigation scheduling prediction and decision-making focusing on the input features, algorithms used and their applicability in real world conditions. ML performances in terms of accuracy, water conservation compared to fixed or threshold-based methods ...
the problem of attributing publications to their correct authors can be addressed with a variety of machine learning approaches, and the purpose of this project is to compare the performance of these approaches.1 IntroductionThis project investigates the utility of machine learning algorithms in in- ...
Application of machine learning algorithms to the study of noise\n artifacts in gravitational-wave data The sensitivity of searches for astrophysical transients in data from theLIGO is generally limited by the presence of transient, non-Gaussian noiseartifact... R Biswas,L Blackburn,J Cao,... -...
Research Conducted at Persian Gulf University Has Updated Our Knowledge about Machine Learning (Application of Machine Learning Algorithms In Classification the Flow Units of the Kazhdumi Reservoir In One of the Oil Fields In Southwest of Iran) ...
We have applied five ML-based classifiers for the prediction of women's malnutrition based on the significant risk factors. 3.4. Machine learning algorithms In this study, we adopted five ML-based classifiers such as NB, SVM, DT, ANN, and RF for predicting malnourished women. The descriptions...
(CNN)aswellasRankingSVMtobuildarestaurantrecommendationsystemusingtheYelpDataset.Theideaisthat,comparedtoalgorithmsthatarepreviouslycommonlyusedinrecommendationsystem,i.e.Pearsonsimilarityandclusteringalgorithms,theapplicationofmachinelearningtechniquessuchasLDA,CNNandSVMtorecommendationhasbeenanewareaandnotsystematically...