Search Results - (( _ optimization method algorithm ) OR ( variable detection method algorithm ))
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1
A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. …”
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2
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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3
Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…We refer to the new DE algorithm as random variable length crossover DE (rvlx- DE) algorithm. …”
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4
Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri
Published 2023“…Dimension reduction algorithm such as LDA and CNN were applied on the spectra to reduce the number of variables to be trained. …”
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5
Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
6
Power System State Estimation In Large-Scale Networks
Published 2010“…SE requires to use various techniques to ensure validity of the results and to detect and identify sources of errors. The Weighted Least Squares (WLS) method is the most popular technique of SE. …”
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7
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…A spatio-statistical optimization technique that combines the Taguchi statistical method and a spatial plateau objective function (POF) was presented to improve the segmentation procedures for building footprint extraction. …”
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8
New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
Published 2022“…Only one dynamic variable is used as a tuning parameter reducing the complexity of the algorithm. …”
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9
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“…The proposed segmentation is evaluated on real-world clinical data using publicly accessible benchmark clinical liver datasets containing one of the highest numbers of tumors and pathological livers utilized for liver tumor and vasculature segmentation. The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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10
Modelling of cupping suction system based on system identification method
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11
A real-time integrated fire detection and alarm (FDA) system for network based building automation
Published 2017“…This work proposes an improved framework for FDA system to ensure a robust, intelligent network of FDA control panels in real-time. Methods/Analysis: In this work, the shortest path algorithm was chosen for series of buildings connected by a fiber-optic network. …”
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12
Vibration analysis for early detection of bearing failures
Published 2024“…In summary, the combination of RMS acceleration and kurtosis is proposed as a reliable method for identifying bearing faults.…”
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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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14
A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines
Published 2017“…Two back-propagation training algorithms, namely the Levenberg–Marquardt and Bayesian regularization algorithms, and the k-fold cross-validation technique, were employed to train the optimal networks using a training data set. …”
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15
Effect of mixing time and frequency-domain objectives in detecting problematic vibration on unmanned aerial vehicles via barnicle mating optimization
Published 2024“…Problematic vibration detection from Unmanned Aerial Vehicles (UAVs) as a flaw detection and identification (FDI) method has become a viable instrument for evaluating the health and condition of a UAV. …”
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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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An intelligent optical fibre Al(lll) sensor based on advanced materials-sol-gel & polyaniline-porous nanocomposite / Faiz Bukhari Mohd Suah, Abdul Mutalib Md Jani and Mohd Nasir Ta...
Published 2006“…In contrast to traditional methods, the use of this methodology has advantages in terms of a reduction in analysis time and an improvement in the ability of optimization. …”
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18
AI Adoption for Steam Boiler Trip Prevention in Thermal Power Plants
Published 2025“…These findings collectively emphasize the potential of AI-driven methods in enhancing early detection and prevention of boiler trips, thereby contributing to improved operational safety and efficiency. ?…”
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. …”
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20
Groundwater quality assessment and optimization of monitored wells using multivariate geostatistical techniques in Amol-Babol Plain, Iran
Published 2015“…The integration of multivariate statistical methods with geostatistical interpolation techniques revealed that salinity and total and faecal coliforms as time independent variables and hardness as a time dependent variable influenced the groundwater quality in the study area. …”
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