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1181
OLAP Techniques for Approximation and Mining Query Answering
Published 2010-12-01“…Through this research, theoretical concepts which are related with OLAP and Data Warehouse are studied in detail. …”
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1182
An Assessment of Land Use Land Cover Using Machine Learning Technique
Published 2024-12-01“…This research paper presents a comprehensive assessment of the built-up area in Mysuru City over the decade spanning from 2010 to 2020, employing advanced geospatial techniques. …”
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1183
Digital removal of dermal denticle layer using geometric AI from 3D CT scans of shark craniofacial structures enhances anatomical precision
Published 2025-06-01“…The processed scans were reconstructed using bone reconstruction algorithms to enable precise craniofacial measurements. …”
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1184
Optimal Design of the Feeder-Bus Network Based on the Transfer System
Published 2013-01-01“…We extended the demand pattern of M-to-1 in most existing researches to M-to-M. …”
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1185
An Approach for Predicting the Shape and Size of a Buried Basic Object on Surface Ground Penetrating Radar System
Published 2012-01-01“…However, the output target is only hyperbolic representation. This research develops a system to identify a buried object on surface GPR based on decision tree method. …”
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1186
PCA-Kriging-Based Oscillating Jet Actuator Optimization and Wing Separation Flow Control
Published 2024-11-01Get full text
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1187
Robust development of data-driven models for methane and hydrogen mixture solubility in brine
Published 2025-04-01“…In this paper, we aim to form robust data-driven intelligent algorithms founded on various machine learning methods of Support Vector Machine, Random Forest, AdaBoost, Decision Tree, K-nearest Neighbors, Multilayer Perceptron Artificial Neural Network and Convolutional Neural Network to model solubility of hydrogen/methane blend in brine under realistic conditions of underground hydrogen storage projects by utilizing an experimental dataset collected from the existing body of published research. …”
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1188
Energy Demand Forecasting Scenarios for Buildings Using Six AI Models
Published 2025-07-01“…This research addresses a significant gap in energy demand forecasting across three building types by comparing six machine learning algorithms: Artificial Neural Networks, Random Forest, XGBoost, Radial Basis Function Network, Autoencoder, and Decision Trees. …”
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1189
Unsplit Youngs Method for Tracking the Moving Interface of Expansible Grout
Published 2020-01-01Get full text
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1190
A predictive analytics framework for opportunity sensing in stock market
Published 2022-06-01“…Thus research papers in this area suffer from multiple limitations: Very short prediction period from one day to one week, consideration of few stocks only instead of whole of stock market spectrum, exploration of more suitable machine learning algorithms. …”
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1191
Optimizing Energy Forecasting Using ANN and RF Models for HVAC and Heating Predictions
Published 2025-06-01Get full text
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1192
Explainable Anomaly Detection Based on Operational Sequences in Industrial Control Systems
Published 2025-01-01“…Anomaly detection systems, initially implemented for detecting device faults or failures, have increasingly become the focus of research aimed at identifying attack patterns as cyberattack techniques become more sophisticated and intelligent. …”
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1193
FIORA: Local neighborhood-based prediction of compound mass spectra from single fragmentation events
Published 2025-03-01Get full text
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1194
Integrated Evaluation and error decomposition of four gridded precipitation products using dense rain gauge observations over the Yunnan-Kweichow Plateau, China
Published 2024-12-01“…The main findings are as follows: (1) AERA5-Asia, AIMERG, and IMERG-Final show similar precipitation patterns, with ERA5-Land overestimating. While all display minor seasonal variations, AERA5-Asia underestimates summer rain. …”
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1195
An optimized ensemble model with advanced feature selection for network intrusion detection
Published 2024-11-01“…However, these methods often fall short in detecting sophisticated and evolving threats, particularly those involving subtle variations or mutations of known attack patterns. To address this challenge, our study presents the “Optimized Random Forest (Opt-Forest),” an innovative ensemble model that combines decision forest approaches with genetic algorithms (GAs) for enhanced intrusion detection. …”
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1196
Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses
Published 2025-05-01“…Prognostic gene sets were screened using machine learning algorithms to construct a risk model, which was externally validated via GEO database. …”
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1197
Narrowband Theta Investigations for Detecting Cognitive Mental Load
Published 2025-06-01“…Another measure of the signal considered as a discriminator is energy. In this research, it was used just for model comparison. A cognitive load detection algorithm based on these signal metrics was developed and tested on original experimental data. …”
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1198
Predicting climate-driven shift of the East Mediterranean endemic Cynara cornigera Lindl
Published 2025-02-01Get full text
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1199
Spatiotemporal Analysis of Multi-UAV Persistent Search and Retrieval with Stochastic Target Appearance
Published 2025-02-01“…Additionally, we introduce trellis charts for integrated visualization and analysis of combined spatiotemporal patterns. This research builds on a case study developed in a previous case study of multi-UAV PSR-STA. …”
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1200
Integrating digital and narrative medicine in modern healthcare: a systematic review
Published 2025-12-01“…This integrated approach supports technological proficiency and humanistic values, for advancements in digital health to improve rather than displace the interpersonal foundations of patient care. Further empirical research might assess long-term outcomes and guide implementation into curricula, faculty development, and institutional policy.Background: The increasing integration of digital technologies in healthcare, such as electronic health records, telemedicine, and diagnostic algorithms, has improved efficiency but raised concerns about the depersonalization of care. …”
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