3.327 hasil untuk machine learning
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Artikel Jurnal
A 1 km daily soil moisture dataset over China using in situ measurement and machine learning
…a 1 km resolution long-term dataset of soil moisture derived through machine learning trained by the in situ measurements of 1789 stations over China, named SMCI1.0 (Soil Moisture of China by in situ data, version 1.0). Random forest is used as a robust machine learning approach to predict soil…
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Predicting mortality risk in patients with COVID-19 using machine learning to help medical decision-making
In the wake of COVID-19 disease, caused by the SARS-CoV-2 virus, we designed and developed a predictive model based on Artificial Intelligence (AI) and Machine Learning algorithms to determine the health risk and predict the mortality risk of patients with COVID-19. In this study, we used a dataset…
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Machine Learning for Resource Management in Cellular and IoT Networks: Potentials, Current Solutions, and Open Challenges
…In the wake of disruptive IoT with a huge amount and variety of data, Machine Learning (ML) and Deep Learning (DL) mechanisms will play a pivotal role to bring intelligence to the IoT networks. Among other aspects, ML and DL can play an essential role in addressing the challenges of resource…
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Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches
This study analyzes and forecasts the long-term Spatio-temporal changes in rainfall using the data from 1901 to 2015 across India at meteorological divisional level. The Pettitt test was employed to detect the abrupt change point in time frame, while the Mann-Kendall (MK) test and Sen's Innovative…
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Intrusion Detection System Using Machine Learning for Vehicular Ad Hoc Networks Based on ToN-IoT Dataset
…are now interested in adding a high level of security to VANETs. Machine learning (ML) methods were used for constructing a high level of security capabilities based on intrusion detection systems (IDSs). Furthermore, the vast majority of existing research is based on NSL-KDD or KDD-CUP99 datasets…
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State-of-the-art on research and applications of machine learning in the building life cycle
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A Flexible SDN-Based Architecture for Identifying and Mitigating Low-Rate DDoS Attacks Using Machine Learning
…train the intrusion detection system (IDS) in our architecture using six machine learning (ML) models (i.e., J48, Random Tree, REP Tree, Random Forest, Multi-Layer Perceptron (MLP), and Support Vector Machines (SVM)) and evaluate their performance using the Canadian Institute of Cybersecurity (CIC)…
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Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer
…lncRNAs remains largely unexplored. In this study, we develope a machine learning-based integrative procedure for constructing a consensus immune-related lncRNA signature (IRLS). IRLS is an independent risk factor for overall survival and displays stable and powerful performance, but only…
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Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study
…an intrinsic COVID-19 virus genomic signature and uses it together with a machine learning-based alignment-free approach for an ultra-fast, scalable, and highly accurate classification of whole COVID-19 virus genomes. The proposed method combines supervised machine learning with digital signal…
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The rise of machine learning for detection and classification of malware: Research developments, trends and challenges
…state-of-the-art research focus on the development and application of machine learning techniques for malware detection due to its ability to keep pace with malware evolution. This survey aims at providing a systematic and detailed overview of machine learning techniques for malware detection and…
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Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
…civil infrastructures monitoring frameworks has not been fully matured. Machine learning (ML) algorithms are thus providing the necessary tools to augment the capabilities of SHM systems and provide intelligent solutions for the challenges of the past. This article aims to clarify and review the ML…
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Efficient Prediction of Cardiovascular Disease Using Machine Learning Algorithms With Relief and LASSO Feature Selection Techniques
…and this may reduce mortality rates. Identifying risk factors using machine learning models is a promising approach. We would like to propose a model that incorporates different methods to achieve effective prediction of heart disease. For our proposed model to be successful, we have used efficient…
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