204.674 hasil untuk machine learning
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Artikel Jurnal
Machine learning for precision diagnostics of autoimmunity
…industry. We have developed an integration pipeline to enable the use of machine learning for patient classification based on multi-omics data in combination with clinical values and laboratory results. The application of our framework resulted in up to 96% prediction accuracy of autoimmune…
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Machine learning algorithms in air quality modeling
…emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affect the performance of an algorithm, however, it is yet to be known why an algorithm is preferred…
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Recent Advances in Machine Learning in Tribology
Tribology, the study of friction, wear, and lubrication, has been a subject of interest for researchers exploring the complexities of materials and surfaces [...]
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Artikel Jurnal
Improved freezing rain forecast using machine learning
…models. Here a data-driven forecasting method for freezing rain using machine learning technologies is proposed. Observations of weather phenomenon collected from 2 515 national weather stations of China for winter of 2016–2019 and the corresponding atmospheric predictors derived from ERA5…
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How Automated Machine Learning Can Improve Business
Automated Machine Learning (AutoML) is revolutionizing how businesses utilize data, but there seems to be a lack of clarity and a holistic view regarding all its advantages, especially concerning the benefits of AutoML for companies. In order to deeply understand how AutoML can improve businesses…
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Machine learning analysis of fission product yields
…the limitations, especially in scenarios of limited data availability, machine learning models like gaussian process regression (GPR) and gaussian mixture model (GMM) are used for single-fission yield prediction and uncertainty quantification. The application of machine learning techniques…
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SyROCCo: enhancing systematic reviews using machine learning
The sheer number of research outputs published every year makes systematic reviewing increasingly time- and resource-intensive. This paper explores the use of machine learning techniques to help navigate the systematic review process. Machine learning has previously been used to reliably “screen”…
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Predicting Employee Attrition Using Machine Learning Techniques
There are several areas in which organisations can adopt technologies that will support decision-making: artificial intelligence is one of the most innovative technologies that is widely used to assist organisations in business strategies, organisational aspects and people management. In recent…
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Artikel Jurnal
Hydrodesulfurization of Dibenzothiophene: A Machine Learning Approach
…the efficiency of catalysts in the HDS of DBT were investigated using machine learning (ML) algorithms. The conversion of DBT and selectivity was estimated by applying Lasso, Ridge, and Random Forest regression techniques. For the estimation of conversion of DBT, Random Forest and Lasso offer…
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Machine learning on academic education: Bibliometric studies
The use of Machine Learning exhibits significant promise in facilitating advancements in the field of education. It is vital to conduct a comprehensive review of existing research to ascertain the significance of utilizing Machine Learning as a viable approach to enhance educational advancements…
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Artikel Jurnal
SVM Ransomware Detection Using Machine Learning Algorithm
…number of ML models based on the: Random Forest algorithm, Support Vector Machine (SVM) and Gradient boosting algorithm. Ransomware is one of the well-known ways and frequent use which cyber-attackers use in infecting their victims, either through phishing or drive download. Attackers will create…
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MACHINE LEARNING (AI) FOR IDENTIFYING SMART CITIES
…available on the internet. And this by means of different algorithms of machine learning such as Random Forest RF, Artificial Neural Network ANN, Support Vector Machine (SVM), and Gradient Boost (XGB). These algorithms have been compared and evaluated in order to select the best one. The tests…
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Artikel Jurnal
Tunneling Activities Detection Using Machine Learning Techniques
Tunnel establishment, like HTTPS tunnel or related ones, between a computer protected by a security gateway and a remote server located outside the protected network is the most effective way to bypass the network security policy. Indeed, a permitted protocol can be used to embed a forbidden one…
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Artikel Jurnal
Optimized multifidelity machine learning for quantum chemistry
Machine learning (ML) provides access to fast and accurate quantum chemistry (QC) calculations for various properties of interest such as excitation energies. It is often the case that high accuracy in prediction using a ML model, demands a large and costly training set. Various solutions and…
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DEA and Machine Learning for Performance Prediction
…the relative efficiency values of decision units, and then, eleven machine learning models are used to train the absolute efficient frontier to be applied to the performance prediction of new decisions units. To further improve the prediction effect of the models, this paper proposes a training set…
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Evaluating Plant Gene Models Using Machine Learning
…arising during gene model prediction we have developed Truegene, a machine learning approach to classify potential low confidence gene models using 14 gene and 41 protein-based characteristics. Amino acid and nucleotide sequence-based features were calculated for conserved (high confidence) and…
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Predicting Employee Attrition Using Machine Learning Approaches
…needs to be implemented to find the causes of employee attrition and a learning framework to predict employee attrition. This research study aimed to analyze the organizational factors that caused employee attrition and the prediction of employee attrition using machine learning techniques. The…
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Artikel Jurnal Teks lengkap
Machine learning in biohydrogen production: a review
…to realize biohydrogen commercial uptake on a large-scale. Recently, machine learning algorithms have demonstrated the ability to handle large amounts of data while requiring less in-depth knowledge of the system and being capable of adapting to evolving circumstances. This review critically…
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Artikel Jurnal
Designing optimal behavioral experiments using machine learning
…work, we provide a tutorial on leveraging recent advances in BOED and machine learning to find optimal experiments for any kind of model that we can simulate data from, and show how by-products of this procedure allow for quick and straightforward evaluation of models and their parameters against…
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