Search Results - model ((((replication algorithm) OR (function algorithm))) OR (detection algorithm))
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1
A novel deadlock detection algorithm for neighbour replication on grid environment
Published 2012“…The NRGDD is compared with Multi-Cycle of Deadlock Detection and Recovery (MC2DR) algorithm based on the time required for both models to detect two deadlock cycles and using different numbers of transactions. …”
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2
Data-driven multi-fault detection in pipelines utilizing frequency response function and artificial neural networks
Published 2025“…The subsequent data processing stage involved the application of an ANN algorithm for pattern recognition to analyze and classify the acquired data, identifying patterns associated with the replicated fault conditions. …”
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3
Neural network algorithm-based fall detection modelling
Published 2020“…However, the improvement of model accuracy is still needed. This article presents results of modelling for fall detection system by using nonlinear autoregression neural network NARnet algorithm. …”
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4
A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network
Published 2015“…The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. …”
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5
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This research focuses on the parameter estimation, outlier detection and imputation of missing values in a linear functional relationship model (LFRM). …”
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6
March-based diagnosis algorithm for static random-access memory stuck-at faults and transition faults
Published 2012“…Results obtained from simulation validate the generated fault syndromes thus confirmed the ability of this algorithm to detect and distinguish between SAFs and TFs. …”
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7
Model-based hybrid variational level set method applied to lung cancer detection
Published 2024“…This algorithm simplifies the (Local Intensity Clustering) LIC model and devises a new energy functional based on the region-based pressure function. …”
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8
Detecting resource consumption attack over MANET using an artificial immune algorithm
Published 2011“…The Human Immune System (HIS) is considered as a bank of models, functions, and concepts from where Artificial Immune algorithms are inspired. …”
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9
A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network
Published 2018“…The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. …”
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10
Outbreak detection model based on danger theory
Published 2014“…Two outbreak diseases, dengue and SARS, are subjected to a danger theory algorithm; namely the dendritic cell algorithm.To evaluate the model, four measurement metrics are applied: detection rate, specificity, false alarm rate, and accuracy. …”
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11
A Review Paper On Memory Fault Models And Test Algorithms
Published 2021“…In this review paper, functional fault models which may exist in the memory are described, in terms of their definition and detection requirement. …”
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12
The impact of executive function and aerobic exercise recognition in obese children under deep learning
Published 2025“…The OpenPose motion recognition model optimized with STN and Lucas–Kanade optical flow algorithm not only exhibits superior performance in keypoint detection and pose estimation but also positively influences the physical health and functional capacity of children.…”
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13
Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin
Published 2024“…The implementation phase focuses on the deployment of the Decision Tree algorithm and system evaluation through functionality testing. …”
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14
Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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15
A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…The study contributes insights into the importance of pre-processing and feature selection in improving algorithm performance. The findings have implications for developing accurate predictive models and improving diabetes detection.…”
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16
Wood texture detection with conjugate gradient neural network algorithm
Published 2017“…Some experiments have been conducted to analyze the model and system. The experiments are based on artificial neural network (ANN) algorithm that used back propagation and conjugate gradient method of training function in the process of identification. …”
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17
Improved expectation maximization algorithm for Gaussian mixed model using the kernel method
Published 2013“…We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. …”
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18
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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19
Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…Drawing from an extensive review of existing predictive models and cardiovascular health risk factors, this research proposes an enhanced ADAM optimization algorithm, integrated with advanced data processing and feature selection methodologies, to identify and refine key predictors for improved model performance. …”
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20
Enhancing Efficientnet-Yolov4 For Integrated Circuit Detection On Printed Circuit Boards
Published 2024“…Extensive experiments and evaluations demonstrate the proposed algorithm's effectiveness and robustness in complex pcb layouts, as well as its adaptability to varying colour and brightness randomness, surpassing the performance of other pcb inspection models.…”
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