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testing algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
develop » developed (Expand Search)
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121
Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …”
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Multilayer perceptron-based DFE with lattice structure
Published 2001“…The adaptive lattice algorithm is a modification to the one developed by Ling and Proakis (1985). …”
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Multilayer perceptron-based DFE with lattice structure
Published 2001“…The adaptive lattice algorithm is a modification to the one developed by Ling and Proakis (1985). …”
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125
Anomaly Detection Based Framework for Profile Monitoring
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doctoralThesis -
126
Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends
Published 2024“…The k-fold cross-validation technique is used for model training, and the developed neural network-based model is used to investigate the effects of operating parameters on the premixed turbulent flames. …”
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127
Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection
Published 2024“…<p>The increasing accessibility of extensive datasets has amplified the importance of extracting insights from high-dimensional data. However, the task of selecting relevant features in these high-dimensional spaces is made more difficult due to the curse of dimensionality. …”
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128
Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…The complex gas hydrate prevention unit is simulated using the MLPNN model trained by 20 different optimization algorithms. This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. …”
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129
Upgraded SemIndex Prototype Supporting Intelligent Database Keyword Queries through Disambiguation, Query as You Type, and Parallel Search Algorithms
Published 2018“…Various weighting functions and intelligent search algorithms have been developed for that purpose and will be presented here. …”
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130
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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131
Improving Rule Set Based Software Quality Prediction
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132
Indoor Localization Based on Floor Plans and Power Maps
Published 2015“…An indoor localization algorithm that is based on fingerprinting and trilateration is developed. …”
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133
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A Modified PWM Strategy With an Improved ANN Based MPPT Algorithm for Solar PV Fed NPC Inverter Driven Induction Motor Drives
Published 2023“…All the simulation works are carried out in MATLAB/Simulink environment and a reduced scale laboratory prototype of the IMD is built and tested to validate the performance of the proposed THISDPWM technique.…”
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Autonomous Robot Navigation Based On Recurrent Neural Networks
Published 2012Get full text
doctoralThesis -
136
Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021“…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. We show how our algorithm supports the definition of a budget for alignment computation and also augment it with strategies for meta-heuristic optimization and pruning of the search space. …”
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Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering
Published 2024“…It calculates the dimension relevance with various data instances. These further place the relevant dimension samples in one group. …”