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method algorithm » mould algorithm (Expand Search)
using algorithms » cosine algorithm (Expand Search)
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Assessment of Drug-Induced QTc Prolongation in Mental Health Practice: Validation of an Evidence-Based Algorithm
Published 2023“…</p></h3><h3>Methods</h3><h3><p dir="ltr">Following an initial face validity by content experts, a cross-sectional survey of mental health care practitioners with a 4-point Likert-type scale was used to assess the validity of the decision steps on the QTcIP algorithm (QTcIPA) by estimating the content validity index (CVI) and the modified kappa statistic (κ*). …”
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Practical single node failure recovery using fractional repetition codes in data centers
Published 2016“…Hence, a practical solution for node failures is presented by using a self-designed genetic algorithm that searches within the feasible solution space. …”
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Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models
Published 2022“…Deep learning is the most promising algorithm compared to another Machine Learning (ML) algorithm. …”
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A Review of the Genetic Algorithm and JAYA Algorithm Applications
Published 2022“…On the other a well-known and somewhat older evolutionary based method called the Genetic Algorithm with applications is also presented here. …”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
Published 2021“…Moreover, the results of MGWO are compared with seven state-of-art gene selection methods using the same datasets based on classification accuracy and the number of selected genes. …”
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Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare
Published 2007“…To make the process of damage assessment and recovery fast and efficient and in order not to scan the whole log, researchers have proposed different methods for segmenting the log, and accordingly presented different damage assessment and recovery algorithms. …”
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Content-Aware Adaptive Video Streaming Using Actor-Critic Deep Reinforcement Learning
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FarmTech: Regulating the use of digital technologies in the agricultural sector
Published 2023“…<p dir="ltr">Farming relies on the accurate collection and processing of data. Algorithms utilizing artificial intelligence can predict patterns and spot problems, helping farmers make more informed decisions. …”
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Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring
Published 2024“…TTR-GAN comprises cascaded dual-stage 1D Cycle Generative Adversarial Networks (1D-CycleGANs) constructed using Super-ONNs. In the first phase, corrupted wPPG waveforms are blindly restored using a 1D-CycleGAN-based restoration framework. …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…The paper proposes a concurrent job scheduling algorithm in a multi-energy data source environment using Apache Spark. …”
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The automation of the development of classification models and improvement of model quality using feature engineering techniques
Published 2023“…We demonstrated the applicability of feature engineering techniques such as data imputation, transformation (e.g., scaling, centering, etc.), and data balancing using several case studies and the proposed semi-automated framework. …”
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A novel encryption algorithm using multiple semifield S-boxes based on permutation of symmetric group
Published 2023“…The presented algorithm is mainly based on the Shannon idea of substitution–permutation network where the process of substitution is performed by the proposed S<sub>8</sub> semifield substitution boxes and permutation operation is performed by the binary cyclic shift of substitution box transformed data. …”
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Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles
Published 2024“…<p dir="ltr">The control and state estimation of Unmanned Aerial Vehicles (UAVs) provide significant challenges due to their complex and nonlinear dynamics, as well as uncertainties arising from factors such as sensor noise, wind gusts, and parameter fluctuations. Neural network-based methods tackle these problems by accurately approximating unknown nonlinearities through training on input-output data. …”
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Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation
Published 2023“…This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. …”
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Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…”
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