3,327 results for machine learning
Showing 261–280 · 1.11 seconds · RSS
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Journal Article Full text
Precision Irrigation Management Using Machine Learning and Digital Farming Solutions
…paper is to investigate research regarding the integration of different machine learning models that can provide optimal irrigation decision management. This article reviews the research trend and applicability of machine learning techniques, as well as the deployment of developed machine learning…
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Interpretable machine learning with an ensemble of gradient boosting machines
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Multi-Stage Optimized Machine Learning Framework for Network Intrusion Detection
…the security and privacy of their online activities. Several previous machine learning (ML)-based network intrusion detection systems (NIDSs) have been developed to protect against malicious online behavior. This paper proposes a novel multi-stage optimized ML-based NIDS framework that reduces…
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Perspective—Combining Physics and Machine Learning to Predict Battery Lifetime
…we outline several architectures for integrating physics-based and machine learning models that can improve our ability to forecast battery lifetime. We discuss the ease of implementation, advantages, limitations, and viability of each architecture, given the state of the art in the battery and…
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Evaluation of a decided sample size in machine learning applications
BACKGROUND: An appropriate sample size is essential for obtaining a precise and reliable outcome of a study. In machine learning (ML), studies with inadequate samples suffer from overfitting of data and have a lower probability of producing true effects, while the increment in sample size increases…
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Book Chapter Full text
NetFlow Datasets for Machine Learning-Based Network Intrusion Detection Systems
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A review of epileptic seizure detection using machine learning classifiers
…and discovery of the brain-related knowledge is a challenging task. Machine learning classifiers are able to classify EEG data and detect seizures along with revealing relevant sensible patterns without compromising performance. As such, various researchers have developed number of approaches to…
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Groundwater level prediction using machine learning models: A comprehensive review
…two decades, significant progress has been made in GWL prediction using machine learning (ML) models. Several review articles have been published, reporting the advances in this field up to 2018. However, the existing review articles do not cover several aspects of GWL simulations using ML, which…
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Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons
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IntruDTree: A Machine Learning Based Cyber Security Intrusion Detection Model
…is becoming more important. Artificial intelligence, particularly machine learning techniques, can be used for building such a data-driven intelligent intrusion detection system. In order to achieve this goal, in this paper, we present an Intrusion Detection Tree (“IntruDTree”)…
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Crop Monitoring Using Satellite/UAV Data Fusion and Machine Learning
…monitoring using satellite/unmanned aerial vehicle (UAV) data fusion and machine learning. Worldview-2/3 satellite data were tasked synchronized with high-resolution RGB image collection using an inexpensive unmanned aerial vehicle (UAV) at a heterogeneous soybean (Glycine max (L.) Merr.) field…
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Machine learning identifies candidates for drug repurposing in Alzheimer’s disease
…and less expensive option. We present DRIAD (Drug Repurposing In AD), a machine learning framework that quantifies potential associations between the pathology of AD severity (the Braak stage) and molecular mechanisms as encoded in lists of gene names. DRIAD is applied to lists of genes arising…
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Journal Article
MQTTset, a New Dataset for Machine Learning Techniques on MQTT
…role in the cyber-security field: based on innovative algorithms such as machine learning, they are able to identify or predict cyber-attacks, hence to protect the underlying system. Nevertheless, specific datasets are required to train detection models. In this work we present MQTTset, a dataset…
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Secure, privacy-preserving and federated machine learning in medical imaging
…restrictions. AI techniques can help out by offering tools like federated learning to bridge the gap between personal data protection and data utilisation for research and clinical routine, but these tools need to be secure.
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Leakage and the reproducibility crisis in machine-learning-based science
Machine-learning (ML) methods have gained prominence in the quantitative sciences. However, there are many known methodological pitfalls, including data leakage, in ML-based science. We systematically investigate reproducibility issues in ML-based science. Through a survey of literature in fields…
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Artificial intelligence and machine learning in design of mechanical materials
Artificial intelligence, especially machine learning (ML) and deep learning (DL) algorithms, is becoming an important tool in the fields of materials and mechanical engineering, attributed to its power to predict materials properties, design de novo materials and discover new mechanisms beyond…
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Multi-omic machine learning predictor of breast cancer therapy response
…its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T…
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