204.674 hasil untuk machine learning
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Artikel Jurnal
RETAKAFUL CONTRIBUTIONS MODEL USING MACHINE LEARNING TECHNIQUES
…ReTakaful contributions model for the Moroccan Takaful industry via Machine Learning algorithms. We select the best model by comparing the performance of each algorithm. The achieved results of this study demonstrate the potential of using Machine Learning algorithms to compute ReTakaful…
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Artikel Jurnal Teks lengkap
Forecasting Electricity Prices: A Machine Learning Approach
…to improve electricity price forecasting accuracy through the use of a machine learning technique—namely, a novel genetic programming approach. Drawing on empirical data from the largest EU energy markets, we propose a forecasting model that considers variables related to weather conditions, oil…
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Artikel Jurnal Teks lengkap
Research Progress of Gliomas in Machine Learning
…of biomedical publications has led to the advent of the big-data era. Machine learning methods were applied as possible approaches to speed up the data mining processes. In this article, we reviewed the present situation and future orientations of machine learning application in gliomas within the…
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Artikel Jurnal
AN IMPROVISED VIDEO ENHANCEMENT USING MACHINE LEARNING
…objective clarity or its more subjective qualities, we are interested in learning how we might improve its overall quality.
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Artikel Jurnal
Breakout Stocks Identification using Machine Learning Approaches
…properly, it can help one to invest efficiently. We have used multiple machine learning approaches as ML models can offer more effective predictions compared to other methods due to the ability to learn and adapt from dataset information. In our experiment, the models have yielded very good results.
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Artikel Jurnal Teks lengkap
Optical Cloud Pixel Recovery via Machine Learning
Remote sensing derived Normalized Difference Vegetation Index (NDVI) is a widely used index to monitor vegetation and land use change. NDVI can be retrieved from publicly available data repositories of optical sensors such as Landsat, Moderate Resolution Imaging Spectro-radiometer (MODIS) and…
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Artikel Jurnal
Machine learning for semi-automated scoping reviews
…thousands of publications. To this end we leverage modern representation learning algorithms based on transformer models and established clustering methods to discover evidence maps, key themes within the data, knowledge gaps within the literature, and assess the feasibility of follow-on systematic…
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Artikel Jurnal
Weighted Machine Learning for Spatial-Temporal Data
Applying machine learning techniques to spatial-temporal data poses the question that how the recorded location and time for training samples should contribute to the training and testing process. The prior knowledge of how spatial-temporal phenomena are autocorrelated cannot be properly captured…
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Artikel Jurnal
Machine-learning atomic simulation for heterogeneous catalysis
Abstract Heterogeneous catalysis is at the heart of chemistry. New theoretical methods based on machine learning (ML) techniques that emerged in recent years provide a new avenue to disclose the structures and reaction in complex catalytic systems. Here we review briefly the history of atomic…
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Artikel Jurnal
Demonstration of quantum advantage in machine learning
…and a highly noisy system. The team solved a particular problem, known as learning parity with noise, using a five-qubit superconducting quantum processor. Counting the number of times that the processor runs, they demonstrate that the implemented quantum algorithm finds the solution much faster…
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Artikel Jurnal
Classifying grains using behaviour-informed machine learning
Abstract Sorting granular materials such as ores, coffee beans, cereals, gravels and pills is essential for applications in mineral processing, agriculture and waste recycling. Existing sorting methods are based on the detection of contrast in grain properties including size, colour, density and…
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Artikel Jurnal
Machine Learning Techniques to Analyze Operator’s Behavior
…airline system and recovery solver extensively and to identify various machine learning algorithms that can be used to answer the following questions: "Will, the operator, use the recovery solver?" and "If the operator uses the recovery solver, which solution will she prefer?" In this paper, we…
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Artikel Jurnal
Version-Wide Software Birthmark via Machine Learning
…The proposed software birthmark is a binary-classification model of a machine learning algorithm based on imported and exported function names extracted from different-version executable files. To evaluate the performance of version-wide software birthmarks, our experiments include 138 versions of…
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Artikel Jurnal
Emulating complex simulations by machine learning methods
Abstract Background The aim of the present paper is to construct an emulator of a complex biological system simulator using a machine learning approach. More specifically, the simulator is a patient-specific model that integrates metabolic, nutritional, and lifestyle data to predict the metabolic…
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Artikel Jurnal
Machine Learning based Optical Proximity Correction Techniques
…the research and design for latest technological nodes. The emergence of machine learning technologies inspires novel OPC algorithms. More accurate forward simulation of the lithographic process and single turn optimization methods are enabled by the machine learning based OPC techniques. We…
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Artikel Jurnal
Machine Learning Techniques for 5G and Beyond
…of 6G systems will be the use of Artificial Intelligence (AI) and Machine Learning (ML) for such wireless networks. Every component and building block of a wireless system that we currently are familiar with from our knowledge of wireless technologies up to 5G, such as physical, network and…
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Artikel Jurnal
AUTOMATED CRYPTOCURRENCIES PRICES PREDICTION USING MACHINE LEARNING
…price recorded daily over the period of 6 months. We applied some machine-learning algorithms to predict the daily price change of cryptocurrencies.
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