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181
A machine learning approach for localization in cellular environments
Published 2018“…A machine learning approach is developed for localization based on received signal strength (RSS) from cellular towers. …”
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182
Machine Learning Model for a Sustainable Drilling Process
Published 2023Get full text
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183
A Machine Learning Approach to Predicting Diabetes Complications
Published 2021Get full text
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EEG Signal Processing for Medical Diagnosis, Healthcare, and Monitoring: A Comprehensive Review
Published 2023“…The study of reliable feature extraction and classification algorithms is crucial for a more accurate analysis of EEG signals. …”
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An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network
Published 2021“…Moreover, they can be combined with medical knowledge to improve decision‐making effectiveness, adaptability, and transparency. A performance comparison between the DNN algorithm and some well‐known machine learning techniques as well as the state‐of‐the‐art methods is presented. …”
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Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context
Published 0024“…A dataset generated by a digital learning platform used by a private school in Jordan is utilised. …”
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189
Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Alg...
Published 2023“…In this paper, the scheduling and management framework of an energy hub (EH) is presented with the aim of energy profit maximization in partnership with electricity, natural gas, and district heating networks (EGHNs) considering the coordinated multi-energy management based on the day-ahead market. The optimum capacity of EH equipment, including photovoltaic and wind renewable energy sources, a combined heat and power system (CHP), a boiler, energy storage, and electric vehicles is determined in the day-ahead market using the improved Fick’s law algorithm (IFLA), considering the energy profit maximization and also satisfying the linear network and hub constraints. …”
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190
An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
Published 2021“…First, the NARXNN model acquires the data to generate a residual error vector. Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”
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191
Fast Methods Fbr Split Codebooks
Published 2020“…The method is based on a family of fractals called Space-Filling Curves (SFC). …”
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192
Artificial Intelligence for Cochlear Implants: Review of Strategies, Challenges, and Perspectives
Published 2024“…The process involves receiving the speech signal in analog form, followed by various signal processing algorithms to make it compatible with devices of limited capacities, such as cochlear implants (CIs). …”
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A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
Published 2025“…The increase in imagery data has in turn created a demand for automated detection and classification using deep neural network-based techniques. …”
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194
Approximation algorithms inspired by kernelization nethods
Published 2017“…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of reduction rules and combinatorial insights. …”
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Bee Colony Algorithm for Proctors Assignment.
Published 2015“…The results also show that the Bee Colony algorithm outperforms other methods on most subject problems.…”
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198
Scalable Parallel Algorithms for FPT Problems
Published 2006“…Algorithmic methods based on the theory of fixed-parameter tractability are combined with powerful computational platforms to launch systematic attacks on combinatorial problems of significance. …”
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Improvement Algorithm for Limited Space Scheduling
Published 2001“…The model characterizes resource space requirements over time and establishes a time-space relationship for each activity in the schedule, based on alternative resource levels. An example illustrates the presented algorithm that generates a feasible space schedule.…”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…Our algorithm first performs a feature selection step to define differentiable SNPs. …”
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