204.674 hasil untuk machine learning
Menampilkan 361–380 · 1,32 detik · RSS
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Artikel Jurnal
Trimodal machine learning based biometrics system
Abstract Biometrics-based authentication systems have recently been considered as one of the safest methods to secure our data or possessions. In the literature, the solutions based on one or two measurable traits are broadly described. There was also claim that more features than two can make the…
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Artikel Jurnal
Soil liquefaction assessment using machine learning
…Logistic Regression (LR), Multilayer Perceptron (MLP), Support Vector Machine (SVM) and eXtreme Gradient Boosting (XGBoost) algorithms. Feature importance methods consist of permutation and Shapley Additive exPlanations (SHAP) importances along with the used model's built-in feature importance…
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Artikel Jurnal
Integrating Machine Learning and Educational Robotics
…training and classification phases, enhancing students' understanding of machine learning (ML). The results showed that students grasped both the functioning of the WiSARD algorithm and the mathematical principles behind it. Additionally, the activities fostered reflection on ethical concerns…
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Artikel Jurnal
Searching for ribbons with machine learning
We apply Bayesian optimization and reinforcement learning to a problem in topology: the question of when a knot bounds a ribbon disk. This question is relevant in an approach to disproving the four-dimensional smooth Poincaré conjecture; using our programs, we rule out many potential…
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Artikel Jurnal
Machine learning discovers new champion codes
Abstract Linear error-correcting codes form the mathematical backbone of modern digital communication and storage systems, but identifying champion linear codes (linear codes achieving or exceeding the best known minimum Hamming distance) remains challenging. By training a transformer to predict…
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Artikel Jurnal
Comparative analysis of machine learning classifiers
This study presents a comparative analysis of five machine learning classification algorithms: support vector machine (SVM), multilayer perceptron (MLP), classification and regression tree (CART), k-nearest neighbors algorithm (K-NN), and naive Bayes classifier (NB) across four datasets from…
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Artikel Jurnal Teks lengkap
The Machine Learning Method of PIDVCA
Building a dynamic collision knowledge base of self-learning is one of the core contents of implementing "personified intelligence" in Personifying Intelligent Decision-making for Vessel Collision Avoidance (short for PIDVCA). In the paper, the machine learning method of PIDVCA combined with…
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Artikel Jurnal
Machine learning for bridge wind engineering
…of the state space and action space of the agent in active control. Machine Learning (ML) has been shown versatile for various modeling and control tasks in bridge wind engineering due to its excellent ability to automatically extract space features efficiently and make wonderful decisions facing…
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Artikel Jurnal
Interpretable machine learning for shoreline forecasting
Abstract Machine learning has revolutionized scientific modeling, providing breakthroughs in fields ranging from weather prediction to protein folding. However, its adoption in physics-based domains remains limited due to the lack of interpretability in traditional black-box models. In…
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Artikel Jurnal
Machine Learning-Based Water Quality Prediction
…and predict water potability accurately and in real-time. This study used machine learning models to predict water potability based on quality features such as potential of Hydrogen (pH) value, hardness, solids content, chloramines, sulfate, and conductivity. Potability is determined based on the…
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Artikel Jurnal Teks lengkap
Machine Learning for Daylight Performance Prediction
Machine learning methods are increasingly applied in daylight performance assessment due to their ability to model complex nonlinear relationships within large datasets while offering substantially faster predictions than conventional simulation workflows. Within this framework, deep learning…
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Artikel Jurnal Teks lengkap
Machine Learning Framework for Algorithmic Trading
…such nuance. This study proposes an automated trading system based on machine learning that uses technical analysis as well as sentiment factors for better decision-making. Historical OHLCV stock price data from 2000 to 2025 was augmented with financial indicators such as SMA, EMA, RSI, and…
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Artikel Jurnal
Introversion-Extraversion Prediction using Machine Learning
…for their benefit. This study compares and evaluates several machine learning models and dataset balancing methods to predict the introversion-extraversion personality based on the survey result conducted by Open-Source Psychometrics Project. The dataset was balanced using three balancing methods…
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Artikel Jurnal Teks lengkap
Milk Quality Detection Using Machine Learning
Poor-quality milk and the use of chemicals in it can lead to serious health problems, including various diseases and, in some cases, even death for those who consume it. In our society, using such products or contaminated milk that contains chemicals or is of bad quality, often with water or other…
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Artikel Jurnal Teks lengkap
Obesity Prediction Using Machine Learning Algorithms
Accurate forecasting and management are crucial as obesity represents a global health issue linked to many chronic diseases. This research examines the use of machine learning algorithms such as Decision Tree, Random Forest, K-NN (K Nearest Neighbor), and Naive Bayes for predicting obesity by using…
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Artikel Jurnal Teks lengkap
COVID-19 Prediction Using Machine Learning
…and develop predictive models. This study examines the use of various machine learning techniques for the prediction of COVID-19 such as time series analysis, regression models, and classification techniques. This paper further addresses the problems and constraints of applying the ML model to this…
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Artikel Jurnal Teks lengkap
Stroke Prediction Using Machine Learning Algorithms
…datasets causes biased predictions and inferior classification accuracy, machine learning (ML) techniques have shown potential in stroke prediction. We used the Synthetic Minority Oversampling Technique (SMOTE) to balance datasets and lessen bias in order to address these problems. Furthermore, we…
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Artikel Jurnal
Is machine learning “revolutionising” the Arts?
…been considered automation-proof. Until recently––as recent successes in machine learning (ML) research in the past ten years have given rise to a new wave of interest in the complete automatability of creativity, a final frontier for a maximalist vision for AI-driven automation. Narratives…
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Artikel Jurnal
Machine learning the 6d supergravity landscape
Abstract In this paper, we apply both supervised and unsupervised machine learning algorithms to the study of the string landscape and swampland in 6-dimensions. Our data are the (almost) anomaly-free 6-dimensional N $$ \mathcal{N} $$ = (1, 0) supergravity models, characterised by the Gram matrix…
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