Search Results - (( data estimation method algorithm ) OR ( case generation method algorithm ))
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Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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Kalman filter based impedance parameter estimation for transmission line and distribution line
Published 2019“…To demonstrate the efficiency of the new proposed method, a case study of simulated distribution line in UMP is also considered. …”
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Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty
Published 2025“…The proposed method is assessed using aging data from the NASA battery dataset. …”
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Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins
Published 2024“…So, in this research, a real-time flood inundation map (FIM) is used to develop the ML-based visualization (ML_V) method to characterize the collected dataset. Additionally, to predict the flood depth, a trained Decision Tree (DT)-based sorting algorithm is used in this method. …”
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Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model
Published 2000“…A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. …”
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Case Study: University Lecture Timetabling Without Pre-registration Data
Published 2017“…Data pre-processing algorithm was carried out to predict course registration. …”
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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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Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems
Published 2009“…In each case study, the neural network is fed with the normalized energies of the DC, the fundamental and the first four harmonics of the faulted voltages, effectively trained with a set of training data, and verified with a dedicated testing data obtained from fault voltage signals generated on IEEE 14-bus electric system model. …”
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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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Compression of Three-Dimensional Terrain Data Using Lifting Scheme Based on Second Generation Wavelets
Published 2006“…The newly developed algorithm was applied to compress Light Detection and Ranging (LIDAR) data to check the efficiency of the program. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment
Published 2011“…In the case of real datasets, the proposed method yields 12.16% average misclassification error while the average misclassification error for five different methods GAM, TSY, NWKNN, DWM and FISH is 19.54%. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…The Moran I index using distance decay method to generate the weight gave a spatial autocorrelation of -0.33. …”
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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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Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…The uncertainties of the output power of wind turbine generators are modelled based upon the scenario-based method and data mining techniques. …”
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Channel Modelling and Estimation in Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing Wireless Communication Systems
Published 2008“…The second issue addressed in this thesis is the channel estimation in MIMO OFDM systems. New time-domain (TD) adaptive estimation methods based on recursive least squares (RLS) and normalized least-mean squares (NLMS) algorithms are proposed. …”
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Computerised Faculty Course Timetabling with Student Sectioning
Published 2016“…Data pre-processing algorithm was carried out to predict course registration based on students' curriculum course plan and previous examination result. …”
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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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