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221
A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants
Published 2006“…The U-model utilizes only past data for plant modelling and standard root solving algorithm for control law formulation. …”
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222
Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS
Published 2018“…To do so, we design and construct a semantic-aware inverted index structure called SemIndex, extending the standard inverted index by constructing a tightly coupled inverted index graph that combines two main resources: a semantic network and a standard inverted index on a collection of textual data. We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
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223
Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning
Published 2022Get full text
doctoralThesis -
224
Modeling of Chlorophyll-a and Eutrophication Indicators in the Dubai Creek Area using Remote Sensing
Published 2015Get full text
doctoralThesis -
225
Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models
Published 2023“…For the basic machine learning algorithms, LR, NB, SVM, RF, DT, MLP, AdaBoost, GBoost, and an ensemble model of machine learning classifiers were used. …”
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226
Using artificial bee colony to optimize software quality estimation models. (c2015)
Published 2016“…In this thesis, we propose a novel heuristic based on Artificial Bee Colony (ABC) to optimize rule-based software quality prediction models. We validate our technique on data describing maintainability and reliability of classes in an Object-Oriented system. …”
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masterThesis -
227
Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices
Published 2025“…The methodology involves data preparation with <u>imputation</u> and normalization, followed by training 9 supervised ML models. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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230
C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments
Published 2023“…The aim of streaming conformance checking is to find dis crepancies between process executions on streaming data and the refer ence process model. The state-of-the-art output from streaming confor mance checking is a prefix-alignment. …”
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Single channel speech denoising by DDPG reinforcement learning agent
Published 2025“…It achieves this performance by utilizing data that is 7 times smaller than that required by other models. …”
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Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper
Published 2025“…<h3>Background</h3><p dir="ltr">Machine learning (ML) models can enhance patient–nurse assignments in healthcare organisations by learning from real data and identifying key capabilities. …”
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235
Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation
Published 2023“…Additionally, a clustering algorithm with a fuzzy membership function is implemented, allowing the robots to advance in accordance with predefined clusters and arrive at their starting place within a predetermined amount of time. …”
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Integration of Textural and Material Information into BIM Using Spectrometry and Infrared Sensing
Published 2015Get full text
doctoralThesis -
238
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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System
Published 2020Get full text
doctoralThesis -
240
Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends
Published 2024“…Based on previous 3D numerical analyses, this study aims to develop data-driven machine learning (ML) models for predicting the flame radius evolution and turbulent flame speeds for diesel, gas-to-liquids (GTL), and their 50/50 blend (by volumetric composition) under different thermodynamic and turbulence operating conditions. …”