Search alternatives:
encoding algorithm » cosine algorithm (Expand Search)
models algorithm » mould algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
search » research (Expand Search)
encoding algorithm » cosine algorithm (Expand Search)
models algorithm » mould algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
search » research (Expand Search)
-
201
-
202
Energy-aware adaptive compression for mobile devices. (c2009)
Published 2009Get full text
Get full text
masterThesis -
203
Practical Multiple Node Failure Recovery in Distributed Storage Systems
Published 2016“…The problem is solved using genetic algorithms that search within the feasible solution space. …”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
204
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. …”
Get full text
Get full text
article -
205
Modelling surface currents in the Eastern Levantine Mediterranean using surface drifters and satellite altimetry
Published 2016“…We present a new and fast method that blends altimetric and drifter positions data in order to predict the surface velocity in the Eastern Levantine Mediterranean. …”
Get full text
Get full text
Get full text
Get full text
article -
206
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. …”
-
207
-
208
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. …”
Get full text
Get full text
Get full text
Get full text
article -
209
Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning
Published 2022Get full text
doctoralThesis -
210
Modeling of Chlorophyll-a and Eutrophication Indicators in the Dubai Creek Area using Remote Sensing
Published 2015Get full text
doctoralThesis -
211
Integration of Textural and Material Information into BIM Using Spectrometry and Infrared Sensing
Published 2015Get full text
doctoralThesis -
212
Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma
Published 2019“…<h3>Background</h3><p dir="ltr">Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. …”
-
213
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. …”
-
214
-
215
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. …”
Get full text
Get full text
Get full text
-
216
-
217
-
218
-
219
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. …”
-
220