بدائل البحث:
processing algorithm » processing algorithms (توسيع البحث)
location algorithm » auction algorithm (توسيع البحث), pollination algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
based location » based population (توسيع البحث)
element » elements (توسيع البحث)
processing algorithm » processing algorithms (توسيع البحث)
location algorithm » auction algorithm (توسيع البحث), pollination algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
based location » based population (توسيع البحث)
element » elements (توسيع البحث)
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301
Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
منشور في 2023"…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
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302
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303
Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques
منشور في 2024"…The sensors are unbiased radars with fixed locations. The first method uses an offline technique based on a global optimizer called the CMA-ES algorithm and the second one uses LSTM in its different forms to learn the online adjustment of the fusion weights between the two tracks. …"
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304
High-order parametrization of the hypergeometric-Meijer approximants
منشور في 2023"…<p>In this work, we introduce an extension to the hypergeometric algorithm we developed before for the resummation of divergent series.The extension overcome the time-consuming problem we face in the parametrization process of the hypergeometric approximants. …"
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305
UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices
منشور في 2019"…Then, we develop an effective sub-optimal algorithm based on successive convex approximation in order to obtain results for larger network scenarios. …"
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article -
306
Applying urban parametric design optimisation processes to a hot climate: Case study of the UAE
منشور في 2014"…An urban area in Dubai was selected to act as the case study location for this project. An in-depth analysis was carried out between the base case and the optimised case. …"
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307
Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT)
منشور في 2015"…Decision making and/or Decision Support Systems (DSS) using intelligent techniques like Genetic Algorithm and fuzzy logic is becoming popular in many new applications. …"
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conferenceObject -
308
Deep Reinforcement Learning for Resource Constrained HLS Scheduling
منشور في 2022"…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …"
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masterThesis -
309
A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer
منشور في 2019"…Second, the pre- and post-processed images were encrypted with a new encryption algorithm in the microcomputer environment. …"
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310
The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review
منشور في 2022"…The study selection process was carried out in three phases: study identification, study selection, and data extraction. …"
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311
Face Flow: Constrained Optical Flow Framework for Faces
منشور في 2020احصل على النص الكامل
doctoralThesis -
312
Benchmark on a large cohort for sleep-wake classification with machine learning techniques
منشور في 2019"…However, the largest experiments conducted to date, have had only hundreds of participants. In this work, we processed the data of the recently published Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study to have both PSG and actigraphy data synchronized. …"
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313
Improving Rule Set Based Software Quality Prediction
منشور في 2003احصل على النص الكامل
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article -
314
An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems
منشور في 2024"…Feature selection (FS) is the activity of defining the most contributing feature subset among all used features to improve the superiority of datasets with a large number of dimensions by selecting significant features and eliminating redundant and irrelevant ones. Therefore, this process can be seen as an optimization process. The primary goals of feature selection are to decrease the number of dimensions and enhance classification accuracy in many domains, such as text classification, large-scale data analysis, and pattern recognition. …"
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315
Phased Array Technique for Brain Source Localization
منشور في 2012احصل على النص الكامل
doctoralThesis -
316
A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
منشور في 2025"…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…"
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317
The bus sightseeing problem
منشور في 2023"…A mixed-integer programming formulation for the BSP is provided and solved by a Benders decomposition algorithm. For large-scale instances, an iterated local search based metaheuristic algorithm is developed with some tailored neighborhood operators. …"
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318
Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles
منشور في 2017"…The identified a priori knowledge is used to implement an optimal Kalman filter, a multi-hypothesis Kalman filter, and a variant of the full information estimator (moving horizon estimator) to the problem at hand. The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. …"
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319
Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea
منشور في 2018"…Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential ensemble data assimilation framework is challenging due to the exponential growth in the number of particles. …"
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article -
320