Search Results - (( data estimation methods algorithm ) OR ( variable generation using algorithm ))*
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1
A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023“…This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). …”
Conference paper -
2
Fuzzy Type-1 Triangular Membership Function Approximation Using Fuzzy C-Means
Published 2020“…Though membership functions are determined through expert's opinion, however, the one estimated through heuristic algorithms is the preferable methods. …”
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3
Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission
Published 2011“…The new algorithm is capable of producing a high data rate and at the same time a better quantization parameter (QP) stability video sequence. …”
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4
DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS
Published 2011“…Graphical User Interface (GUI) has been generated to help apply the ANN model results while an applicable equation can be used for Group Method of Data Handling model. …”
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5
Design of artificial intelligence based speed estimator for DC drives / Pauziah Saleh
Published 2006“…The training took only few minutes on a PC for the 30000 input-output training data . For this purpose, the Lavenberg-Marquardt back propagation algorithm was used. …”
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6
Seismic wave modeling and high-resolution imaging
Published 2022“…Dip frequency filtering (DFF) is a quick and reliable method for preserving diffraction. To suppress data reflection, this algorithm works in the frequency domain by defining a slope filter with respect to dt/dx. …”
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Book -
7
A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm
Published 2015“…The notion of characteristic profiles for the calibration of the model is also coherent with the application of equivalent fatigue loading in generating experimental data for calibration. The model is simple in application with the use of genetic algorithm for model calibration making use of only the material fatigue limit. …”
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8
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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9
Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Data collected were used for the multilevel analysis, Markov Chain Monte Carlo (MCMC) simulation via WinBUGS algorithm and influence diagrams for BBNs. …”
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10
Proving the efficiency of alternative linear regression model based on mean square error (MSE) and average width using aquaculture data
Published 2019“…Multiple linear regressions (MLR) model is an important tool for investigating relationships between several response variables and some predictor variables. This method is very powerful and commonly used in finance, economic, medical, agriculture and many more. …”
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11
Modeling of cupping suction system based on system identification method
Published 2022“…The input and output data were used to create this modeling output variable of the cupping suction system is detected by connecting a differential pressure sensor to the cup, while the input variable is determined by the speed of the pump applied in various locations. …”
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Undergraduates Project Papers -
12
Proving the eficiency of Alternative Linear regression Model Based on Mean Square Error (MSE) and average width using aquaculture data
Published 2019“…Multiple linear regressions (MLR) model is an important tool for investigating relationships between several response variables and some predictor variables. This method is very powerful and commonly used in finance, economic, medical, agriculture and many more. …”
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13
Performance Modeling And Size Optimization Of A Standalone Photovoltaic System
Published 2013“…Furthermore, SAPV components sizing method was formulated with a nonlinear unconstrained optimization technique by using first derivative method. …”
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14
Improved robust estimator and clustering procedures for multivariate outliers detection
Published 2023“…Visual inspection is insufficient to detect outliers in multivariate data, unlike univariate data. One of the methods to detect outliers in multivariate data is by using distance-based methods, which is Mahalanobis distance (MD). …”
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15
High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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16
Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…A generated data where the failure times are taken as exponentially distributed are used to further compare these two parametric models. …”
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17
Development of robust procedures for partial least square regression with application to near infrared spectral data
Published 2021“…The Partial Least Square Regression (PLSR) is a multivariate method commonly used to build a predictive model of Near Infrared (NIR) spectral data. …”
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18
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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19
Multiple equations model selection algorithm with iterative estimation method
Published 2016“…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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Article -
20
The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…It will help the researcher get the fitted graph model, correct data, and estimate the value based on the data’s behaviour. …”
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