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encoding algorithm » cosine algorithm (Expand Search)
mean algorithm » deer algorithm (Expand Search), search algorithm (Expand Search)
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encoding algorithm » cosine algorithm (Expand Search)
mean algorithm » deer algorithm (Expand Search), search algorithm (Expand Search)
data banking » data mining (Expand Search), uae banking (Expand Search), dual banking (Expand Search)
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Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021Subjects: “…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…”
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The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs
Published 2023“…We focus on the combined influence of data encoding, qubit entanglement, and ansatz expressibility in hybrid quantum neural networks (HQNNs) for multi-class classification tasks. …”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…The financial data supply chain is vital to the economy, especially for banks. …”
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Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018)
Published 2018“…Companies, nowadays, rely on systems and applications to automate their business processes and data management. In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …”
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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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The Use of Microwave Tomography in Bone Healing Monitoring
Published 2019Get full text
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A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks
Published 2022“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …”
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Scatter Search algorithm for Protein Structure Prediction
Published 2016“…These candidates undergo evolutionary operations that combine search intensification and diversification over a number of iterations. We evaluate our algorithm on three proteins taken from a Protein Data Bank (PDB). …”
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Evolutionary algorithm for predicting all-atom protein structure
Published 2011“…We evaluate our algorithm on proteins taken from a Protein Data Bank. …”
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Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection
Published 2011“…In order to analyze the performance of machine learning algorithms, data was provided by a bank to be used for educational purposes and shall remain undisclosed. …”
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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. …”
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Scatter search for protein structure prediction. (c2008)
Published 2008Get full text
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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study
Published 2021“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”