Search Results - (( variable interactions _ algorithm ) OR ( variable detection using algorithm ))
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1
Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
Published 2011“…Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. …”
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2
Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…In contrast to the conventional methods which perform detection from a single image, the stenosis detection algorithm using two images from various view angles to avoid false positive (stenosis overestimated) and false negative (stenosis underestimated). …”
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3
HABC: Hybrid artificial bee colony for generating variable T-way test sets
Published 2020“…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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4
HABC: Hybrid artificial bee colony for generating variable T-way test sets
Published 2020“…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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5
Enhancing Harmony Search Metaheuristic Algorithm for Coverage Efficiency, Test Suite Reduction, and Running Time in Combinatorial Interaction Testing
Published 2025“…The Harmony Search (HS) algorithm is a recent metaheuristic that mimics musicians’ improvisation to create pleasant compositions according to aesthetic standards widely used in different areas continuously adjusts solution variables to find the best outcome. …”
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6
Survey on input output relation based combination test data generation strategies
Published 2015“…Over the years, many combinatorial test data generation strategies have been developed supporting uniform and variable strength interactions. Although useful, these existing strategies are lacking the support for Input Output Relations (IOR). …”
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7
A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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8
Survey on input output relation based combination test data generation strategies
Published 2015“…Over the years, many combinatorial test data generation strategies have been developed supporting uniform and variable strength interactions. Although useful, these existing strategies are lacking the support for Input Output Relations (IOR). …”
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9
Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. …”
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10
FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA
Published 2018“…Quantitative analysis was performed using partial least square (PLS) algorithms with the linear regression method. …”
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Evolutionary approach for combinatorial testing of software product lines
Published 2020“…The approaches are (1) adopting an Estimation of Distribution Algorithm approach to aid the construction of a covering array driven by second order feature dependence, and (2) construct a feature configuration dependence graph to assist in building the variable-strength covering array. …”
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12
FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA
Published 2024journal::journal article -
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All-in-1 adverse drug reaction reporting system / Long Chiau Ming … [et al.]
Published 2014“…Values obtained from this algorithm are used in peer reviews to verify the validity of reporter’s conclusion regarding ADRs. …”
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14
Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…This is followed by the clustering of the liver tissues using particle swarm optimized spatial FCM algorithm. …”
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15
Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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16
Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detecti...
Published 2018“…In this study, several models has been created which are from QPS Fledermaus model, BTM model and Slope Variability model. Slope variability model is an algorithm that is being used for detecting terrain roughness. …”
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17
Fault diagnostic algorithm for precut fractionation column
Published 2004“…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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18
Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)
Published 2006“…In this research work, an FDD algorithm is developed using MSPC and correlation coefficients between process variables. …”
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Identification of debris flow initiation zones using topographic model and airborne laser scanning data
Published 2017“…MARSpline multivariate data mining predictive approach was implemented using morphometric indices and topographical derived parameter as independent variables. …”
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20
Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm
Published 2007“…Then the algorithm gathers all the test cases based on the definition occurrence and def-use pair if they cover same definition occurrence of one variable but they don’t cover def-use pair of the same variable. …”
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