204.674 hasil untuk machine learning
Menampilkan 481–500 · 3,46 detik · RSS
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Artikel Jurnal
Decontaminating eukaryotic genome assemblies with machine learning
…organism. Results We introduce a novel application of an established machine learning method, a decision tree, that can rigorously classify sequences. The major strength of the decision tree is that it can take any measured feature as input and does not require a priori identification of…
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Artikel Jurnal
Mining Protein Databases using Machine Learning Techniques
With a large amount of information relating to proteins accumulating in databases widely available online, it is of interest to apply machine learning techniques that, by extracting underlying statistical regularities in the data, make predictions about the functional and evolutionary…
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Artikel Jurnal Teks lengkap
Constraining effective field theories with machine learning
…that combine physics insights, statistical methods, and the power of machine learning. We have developed MadMiner, a new Python package that makes it straightforward to apply these techniques. In example LHC problems we show that the new approach lets us put stronger constraints on theory…
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Artikel Jurnal
Machine Learning Approaches to TCR Repertoire Analysis
…Various data and database platforms are now driving the rapid progress of machine learning for immunological data analysis. Of various topics in immunology, T cell receptor repertoire analysis is one of the most important targets of machine learning for assessing the state and abnormalities of…
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Artikel Jurnal
Mud loss estimation using machine learning approach
…formation. A larger data set, more systematic statistical approach, and a machine-learning algorithm have produced statistical models that give a better prediction of the lost circulation volumes, ECD, and ROP than the previous models for events. This paper presents the new model, validates the key…
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Artikel Jurnal
Algal community structure prediction by machine learning
…on the algal community shifts. This study highlighted the power of machine learning in predicting complex algal community structures and provided insights into the model interpretability.
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Artikel Jurnal Teks lengkap
Machine Learning Applications in Organic Solar Cells
…and optimization of solar cells. One of the mos invaluable approaches is machine learning methods. Machine learning is considered as a new branch of academic science that provides valuable new information by processing exising data. Areas of application of machine learning in the design and…
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Artikel Jurnal Teks lengkap
Thyroid Disease Classification using Machine Learning Algorithms
…based on the information gathered from the dataset taken from the UCI machine learning repository. Machine learning plays a crucial role in the detection of thyroid disease. This paper suggests various machine-learning methods for thyroid detection and diagnosis for thyroid prevention.
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Artikel Jurnal
Investigating ultrafast quantum magnetism with machine learning
We investigate the efficiency of the recently proposed Restricted Boltzmann Machine (RBM) representation of quantum many-body states to study both the static properties and quantum spin dynamics in the two-dimensional Heisenberg model on a square lattice. For static properties we find close…
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Artikel Jurnal
Machine learning-based adaptive CSI feedback interval
…large signaling overhead. To reduce the feedback overhead, we propose two machine learning-based approaches to adjust the CSI feedback interval. We use a deep neural network and reinforcement learning (RL) to decide whether an UE feeds back the CSI. Simulation results show that the RL-based…
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Artikel Jurnal Teks lengkap
Improved Machine Learning Approach for Wavefront Sensing
In the adaptive optics (AO) system, to improve the effectiveness and accuracy of wavefront sensing-less technology, a phase-based sensing approach using machine learning is proposed. In contrast to the traditional gradient-based optimization methods, the model we designed is based on an improved…
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Artikel Jurnal
Machine learning-based prediction of glioma grading.
…by subjectivity and poor reproducibility. This study aimed to develop a machine learning-based prediction model that integrates clinical and molecular characteristics to improve early glioma grading, thereby enhancing diagnostic accuracy and supporting individualized treatment strategies.MethodsAn…
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Artikel Jurnal
Prediction of biological age using machine learning.
…of study. This research utilizes health examination data to propose a machine learning-based biological age prediction model that quantifies physiological age through residual life estimation. The model leverages LightGBM, which shows an 11.40% improvement in predictive performance (R-squared)…
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Artikel Jurnal
Exploring machine learning approaches for precipitation downscaling
…existing spatial downscaling approaches, specifically focusing on machine learning (ML)-based algorithms. Insights into the accuracy of these downscaling techniques were provided based on findings from published validation studies. Additionally, the environmental variables utilized in these…
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Artikel Jurnal
Rewiring climate modeling with machine learning emulators
…expense limits the number and diversity of simulations available. Machine learning-based emulators, statistical surrogates trained on simulator outputs, can replicate components of climate models at orders-of-magnitude lower cost, enabling ensembles and interpolation across scenarios. We argue that…
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Artikel Jurnal Teks lengkap
Machine Learning in Transforming the Food Industry
…setting the futuristic trends in the food sector. The use of different Machine Learning (ML)-based models has demonstrated promising applications in the food processing industry. Processing operations such as drying, frying, cooking, heating, and baking are complex and challenged by multifaceted…
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