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141
An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems
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masterThesis -
142
Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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143
Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm?
Published 2021“…The resulting model achieves an 89% predictive accuracy using historical data. A unique aspect of the model is the incorporation of self-competence, where the model defers when it cannot reasonably make a recommendation. …”
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144
Scalable parallel algorithms for dynamic programming on tree decomposition. (c2017)
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masterThesis -
145
AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques
Published 2023“…This paper proposes a novel automated algorithm for the health monitoring of concrete column base cover degradation based on IoT and the state-of-the-art deep learning framework, Convolutional Neural Network (CNN). …”
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146
Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic
Published 2021“…Therefore, big data analytics field emerged to tame the generated big data, and use it to provide useful insights to the world. …”
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147
The Relation Between Respiratory & Acute Coronary Syndrome Using Data Mining Techniques
Published 2018“…The purpose of this study is to diagnose acute coronary syndrome using the widely available respiratory diagnosing tools and laboratory test results using data mining classification techniques (Decision tree, Gradient boosted tree, Neural Network, and Naïve Bias). …”
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148
Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
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doctoralThesis -
149
A decentralized load balancing strategy for parallel search-three optimization. (c2010)
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masterThesis -
150
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151
Haplotype inference by pure-parsimony using revamped delayed haplotype selection. (c2011)
Published 2011Get full text
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masterThesis -
152
Parallel implementation of clique partitioning using artificial neural networks. (c2000)
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masterThesis -
153
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154
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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155
Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units
Published 2019“…The flags pertaining to 16x16 sub CUs are used as a cover for data embedding, where 6 or 4 message bits are embedded per CU. …”
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157
Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm
Published 2020“…The performance of the EMA-based SHM is presented showing experimental results considering a reduced number of switching angles applied to a specific three-level converter, but the method can be extrapolated to any other three-level converter topology.…”
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158
Sample intelligence-based progressive hedging algorithms for the stochastic capacitated reliable facility location problem
Published 2024“…To manage uncertainty and decide effectively, stochastic programming (SP) methods are often employed. Two commonly used SP methods are approximation methods, i.e., Sample Average Approximation (SAA), and decomposition methods, i.e., Progressive Hedging Algorithm (PHA). …”
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159
A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
Published 2019“…In order to address this issue, in this paper, we propose a novel hybrid approach with both convolutional and recurrent neural networks combined, which is based on the long short-term memory module. Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …”
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160
Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm
Published 2022“…The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. Tuning of the consequent part parameters are accomplished using extreme learning machine. …”