204.674 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
The Machine-Learning-Empowered Gesture Recognition Glove
…of gesture recognition technology. Therefore, this article designs a machine-learning-empowered gesture recognition glove. We fabricate a flexible strain sensor with a sandwich structure, which has high sensitivity and good cycle stability. After the sensors are configured in the knitted gloves…
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Applying Machine Learning to DEM Raster Images
Geospatial data analysis can be improved by using data-driven algorithms and techniques from the machine learning field. The aim of our research is to discover interrelationships among topographical data to support the decision-making process. In this paper, we extracted topographical geospatial…
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Machine learning for membrane design and discovery
Membrane technologies are becoming increasingly versatile and helpful today for sustainable development. Machine Learning (ML), an essential branch of artificial intelligence (AI), has substantially impacted the research and development norm of new materials for energy and environment. This review…
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Machine learning algorithms for predicting air pollutants
…a likelihood of PM2.5 exceeding a pre-defined safety threshold. Multiple machine learning models are explored in this work. Particularly, classification models are implemented based on meteorological data and air pollutant features measured at different altitudes above a ground level. These…
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New Machine Learning Developments in ROOT/TMVA
The Toolkit for Multivariate Analysis, TMVA, the machine learning package integrated into the ROOT data analysis framework, has recently seen improvements to its deep learning module, parallelisation of multivariate methods and cross validation. Performance benchmarks on datasets from high-energy…
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Machine-Learning-Inspired Workflow for Camera Calibration
…and characterizing the calibration outcomes that is inspired by typical machine learning workflows and practical requirements of camera-based measurements. Combining standard calibration tools and the technique of active targets with phase-shifted cosine patterns, we demonstrate that the imaging…
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MACHINE LEARNING TECHNIQUES FOR DETECTING FALSE SIGNATURES
…In this paper we investigate the possibility to use some supervised learning techniques in order to build models capable to accurately perform such an analysis. The results reported during the testing phase of the obtained model are encouraging for further work.
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Human Gait Activity Recognition Machine Learning Methods
…different gait activities within each gait recording by utilizing Machine Learning algorithms. In line with this, various Machine Learning methods were tested and compared to establish the best-performing algorithm for the classification of the recorded gait information. The combination of…
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Unbiased employee performance evaluation using machine learning
…all the factors that justified the unbiased outcome. We utilized a few machine learning tools in this study including the Logistic Regression classifier, the Gaussian Naive Bayes, the Decision Tree classifier, the K-Nearest Neighbors (K-NN), the SVM classification, etc., in order to predict the…
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Applying Machine Learning Techniques to Implementation Science
Machine learning (ML) approaches could expand the usefulness and application of implementation science methods in clinical medicine and public health settings. The aim of this viewpoint is to introduce a roadmap for applying ML techniques to address implementation science questions, such as…
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Machine Learning in Forecasting Motor Insurance Claims
…weather conditions and car sales, and second, we employ a battery of Machine Learning (ML) algorithms (Support Vector Machines—SVM, Decision Trees, Random Forests, and Boosting) to forecast the average (mean) insurance claim per insured car per quarter. Finally, we identify the variables that are…
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Software Requirements Classification Using Machine Learning Algorithms
…shows a comparison among the text feature extraction techniques, and machine learning algorithms to the problem of requirements engineer classification to answer the two major questions “Which works best (Bag of Words (BoW) vs. Term Frequency–Inverse Document Frequency (TF-IDF) vs. Chi Squared…
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Machine learning in nutrient management: A review
In agriculture, precise fertilization and effective nutrient management are critical. Machine learning (ML) has recently been increasingly used to develop decision support tools for modern agricultural systems, including nutrient management, to improve yields while reducing expenses and…
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Hyperautomation in Super Shop Using Machine Learning
…by utilizing natural language processing in real time. We also used machine learning frameworks, such as XGBoost, linear regression, random forest, and hybrid models together, to predict future product demand. In addition, data mining methods, such as the Apriori algorithm, FP growth algorithm, and…
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A Machine Learning Approach for Bitcoin Forecasting
…that a subset is necessary to improve directional accuracy based on a machine learning ensemble. In our experiments, we study which time series and machine learning algorithms deliver the best results. We found that the most relevant time series that contribute to improving directional accuracy are…
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Ransomware Detection Using Machine Learning: A Survey
Ransomware attacks pose significant security threats to personal and corporate data and information. The owners of computer-based resources suffer from verification and privacy violations, monetary losses, and reputational damage due to successful ransomware assaults. As a result, it is critical to…
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Heart disease prediction using machine learning algorithms
…patient outcomes. In this model, we investigate the application of machine learning techniques for anticipating cardiac disease. We investigate a large dataset made up of patient details, such as demographics, medical histories, and clinical measures. It is absolutely mind-blowing to think that…
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Machine-Learning-Based Calibration of Temperature Sensors
Temperature sensors are widely used in industrial production and scientific research, and accurate temperature measurement is crucial for ensuring the quality and safety of production processes. To improve the accuracy and stability of temperature sensors, this paper proposed using an artificial…
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Unsupervised Machine Learning for Improved Delaunay Triangulation
…changed by human construction. In this work, an attempt was made to use machine learning for the optimization of the unstructured triangular meshes formed with Delaunay triangulation in the global ocean field, so that the triangles in the triangular mesh were closer to equilateral triangles, the…
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Machine learning and disease prediction in obstetrics
Machine learning technologies and translation of artificial intelligence tools to enhance the patient experience are changing obstetric and maternity care. An increasing number of predictive tools have been developed with data sourced from electronic health records, diagnostic imaging and digital…
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