Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 12 of 12 for “"isolation forest"”.
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Spectrum Awareness: Deep Learning and Isolation Forest Approaches for Open-set Identification of Signals
Over the next decade, 5G networks will become more and more prevalent in everyday life. This will provide solutions to current limitations by allowing access to bands previously unavailable to civilian communication networks. However, this also provides new challenges primarily for the military …
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Sistema de detección de intrusiones basado en firmas y ML y asistido por LLM
… con algoritmos de aprendizaje automático (Random Forest e Isolation Forest) y modelos IA (LLM). El objetivo es mejorar la detección de anomalías en el tráfico de red, así como la generación de explicaciones automáticas que sean comprensibles en el análisis de las alertas. La propuesta se validará …
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Using Multi-Source Data to Assess the Dynamics of Socioeconomic Development in Africa
… Imaging Radiometer Suite (VIIRS) NTL and the Isolation Forest (iForest) machine learning algorithm for more intelligent data processing to capture human activities. I use machine learning and NTL data to map gross domestic product (GDP) at 1 km2. I then use these data products to derive …
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An Axiomatic Perspective on Anomaly Detection
… problem with a commonly used method called Isolation Forest, related to infinite bands of space likely to be labelled as inliers that extend infinitely far away from the training data. Additionally, we experimentally demonstrate that another common method, Local Outlier Factor, is vulnerable …
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Detección de Anomalías de Precio en Comercio Electrónico
… un modelo base, regresión logística, Random Forest e Isolation Forest. El análisis exploratorio se realizó sobre una base de datos con más de dos millones de registros de cambios de precios, identificando patrones y distribuciones en diferentes verticales de negocio. Los modelos fueron …
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Graph neural network approaches and real-time unsupervised learning for anomaly detection in vehicular networks
… methods (One-Class SVM, Local Outlier Factor, Isolation Forest, and Elliptic Envelope). The proposed approach incorporates centroid repulsion, dynamic buffer normalization, and outlier-score-based thresholding, enabling adaptive detection without labeled data. Experiments on seven large-scale …
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Circular chemistry through network science and optimisation on big data
… on their position within the network and an isolation forest outlier detection algorithm is employed to identify the key molecules. To assess pathways within network structures, chemical heuristics with following network optimisation are presented. This work introduces Petri net optimisation …
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Advanced AI techniques for comprehensive traffic incident analysis: enhancing incident duration prediction and accident risk forecasting
… detection techniques like One-Class SVM and Isolation Forest into the prediction models. Exploration of Data Fusion Techniques: A key contribution of this research is the exploration of data fusion. By integrating different data types, including traffic flow information, textual incident …
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Edge-Based Anomaly Detection for IoMT: A Lightweight Unsupervised Model and SIEM Integration
… and Event Management (SIEM) workflows. An Isolation Forest model is trained using baseline telemetry that represents normal device behavior and then deployed in inference-only mode at the edge, where the model scores new events without retraining or updating parameters during operation. …
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Beyond Limits: Detecting Anomalies in Sparse, High-dimensional Data
Anomaly detection is a critical aspect of data-driven decision-making, particularly in high-stakes areas such as fraud detection and identifying manufacturing defects. However, the proprietary nature and specialized use cases of such data often result in data that is both high-dimensional and has …
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On Mining Time Series Data with Random Forest Models: Perspectives from Classification, Anomaly Detection, and Distance Measures
L'abstract è presente nell'allegato / the abstract is in the attachment
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Deep Learning Empowered Unsupervised Contextual Information Extraction and its applications in Communication Systems
There has been an astronomical increase in data at the network edge due to the rapid development of 5G infrastructure and the proliferation of the Internet of Things (IoT). In order to improve the network controller's decision-making capabilities and improve the user experience, it is of paramount …