204.674 hasil untuk machine learning
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Artikel Jurnal
International agricultural trade forecasting using machine learning
Focusing on seven major agricultural commodities with a long history of trade, this study employs data-driven analytics to decipher patterns of trade, namely using supervised machine learning (ML), as well as neural networks. The supervised ML and neural network techniques are trained on data until…
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A machine learning-based lithologic mapping method
In this study, a gradient boosting decision tree (GBDT)-based lithologic mapping method constituted by field survey and machine learning is introduced. The Duolong mineral district, Tibet, China is currently chosen for model test. During the practical application, geochemical data at a 1:50000…
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Artikel Jurnal
Prediction of concrete porosity using machine learning
Porosity is an important indicator of the durability performance of concrete. The objective of this study is to apply machine learning methods to empirically predict the porosity of high-performance concrete containing supplementary cementitious materials. The assembled database for concrete…
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Ozone Level Prediction with Machine Learning Algorithms
…level exceeds a certain threshold, risks would be exacerbated. Using machine learning algorithms can help to reduce risks, making inferences from earlier obtained data even for situations, which have not encountered before. In this study, a two-phased hybrid machine learning algorithm is proposed…
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Artikel Jurnal
Materials discovery and design using machine learning
…for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. In this review, we first outline the typical mode of and basic procedures for applying…
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Artikel Jurnal
Mitigating urinary incontinence condition using machine learning
…consequences. Objective This paper proposes a framework based on machine learning for predicting urination time, which can benefit people with various degrees of UI. Method A total of 850 data points were self-recorded by 51 participants to investigate how different factors impact urination time…
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Artikel Jurnal Teks lengkap
Machine Learning Based Automatic Leaf Diseases Detection
The method for applying machine learning to automatically detect leaf diseases is presented in this paper. A convolutional neural network was used to extract pertinent features from leaf image datasets that included healthy and diseased leaves. The dataset was compiled and pre-processed. Accuracy…
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Artikel Jurnal
Forest fire management using machine learning techniques
As per the latest survey produced by the Forest Survey, the forest cover is 19.27% of the geographic area. According to this report every country can meet the human needs of 16% of the world’s population from the 1% of the world’s forest resource. The Forest Survey said that 90% of the forest fires…
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Artikel Jurnal
Machine Learning in Point of Care Ultrasound
…assessments at the patient’s bedside. These assessments often rely on machine learning algorithms as a means of interpreting medical images.
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Artikel Jurnal
Predicting heart disease using machine learning algorithms
Increasing the accuracy of detecting heart disease is widely studied in the field of machine learning. Such a study is intended to prevent large costs in the field of healthcare and is the reason for the misdiagnosis. As a result, various methods of analyzing disease factors were proposed, aimed at…
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Artikel Jurnal
Inferred networks, machine learning, and health data.
This paper presents a network science approach to investigate a health information dataset, the Sexual Acquisition and Transmission of HIV Cooperative Agreement Program (SATHCAP), to uncover hidden relationships that can be used to suggest targeted health interventions. From the data, four key…
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Artikel Jurnal
Using machine learning for healthcare treatment planning
We present a methodology for using machine learning for planning treatments. As a case study, we apply the proposed methodology to Breast Cancer. Most of the application of Machine Learning to breast cancer has been on diagnosis and early detection. By contrast, our paper focuses on applying…
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Artikel Jurnal
Technology readiness levels for machine learning systems
The development of machine learning systems has to ensure their robustness and reliability. The authors introduce a framework that defines a principled process of machine learning system formation, from research to production, for various domains and data scenarios.
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Artikel Jurnal
Use of Machine Learning Methods in Psychiatry
Machine learning methods, which are becoming more and more popular in artificial intelligence and data analysis, provide learning from data in many different fields. In the studies conducted in the field of health, these methods support healthcare professionals and physicians. Psychiatry is one of…
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Artikel Jurnal Teks lengkap
Technology Opportunity Analysis Based on Machine Learning
The sustainable growth of a company requires a differentiated research and development strategy through the discovery of technology opportunities. However, previous studies fell short of the need for utilizing outlier keywords, based on approaches from various perspectives, to discover technology…
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Artikel Jurnal Teks lengkap
COVID-19 Outbreak Prediction with Machine Learning
…models need to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to susceptible–infected–recovered (SIR) and susceptible-exposed-infectious-removed (SEIR) models. Among a wide range of machine…
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Artikel Jurnal Teks lengkap
Machine-Learning Classification of Pulse Waveform Quality
…The present study aimed to determine the effectiveness of using machine-learning analysis in discriminating between high-quality and low-quality pulse waveforms induced by applying different contact pressures. Radial blood pressure waveform (BPW) signals were measured noninvasively in healthy young…
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