Search Results - (( data distribution function algorithm ) OR ( water distribution process algorithm ))
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Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
Published 2024“…The leakage fault cases verify the algorithm�s applicability and complete the correlation diagnosis of water wall leakage fault. …”
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Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
Published 2018“…Signal processing is an important tool to analyse non-stationary and non linear data. …”
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Development of Intelligent Leak Detection System Based on Artificial Pressure Transient Signal Using Integrated Kurtosis-Based Algorithm for Z-Filter Technique (I-Kaz) / Hanafi.M.Y...
Published 2017“…HHT is a way to decompose a signal into intrinsic mode function (IMF). However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method which is Hilbert Transform (HT). …”
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Development of intelligent leak detection system based on artificial pressure transient signal using integrated Kurtosis-based Algorithm for Z-filter Technique (I-Kaz)
Published 2017“…HHT is a way to decompose a signal into intrinsic mode function (IMF). However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method which is Hilbert Transform (HT). …”
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Climate change impact on hydrological, sediment, and nutrient in Langat River basin: an assessment using integrated model / Nor Faiza Abd Rahman
Published 2019“…Thus, the adoption of a strategic approach is necessary to planning and simulating the impact of climate change on hydrology, and its component for the respective authority can carry out its function and roles. This research aims are to study the infilling missing data techniques that are fast and reliable, and to speed up the weather data processing generation and impact of climatology on hydrology and its component that influence the development, planning, and management of successful semi-distributed climate assessment modelling in Selangor. …”
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Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…Data pre-processing to transform data to normal distribution before the training, results in better generalization and persistency of ANN models during testing. …”
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Development of electrical resistance tomography applying vertical metallic column
Published 2021“…The cross section image of the bubble phantom was reconstructed using Linear Back Projection (LBP) algorithm after the data collection process was completed. …”
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Grid-based remotely sensed hydrodynamic surface runoff model using emissivity coefficient / Jurina Jaafar
Published 2015“…The development of a hydrodynamic distributed model is designed to simulate discharge and water levels as a function of space and time. …”
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Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M...
Published 2020“…The model is being trained, tested, and validated to differentiate between clean water and polluted water. There were 1 optimized model selected from the classification process. …”
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…In the hierarchical Bayesian approach, the order and coefficients of the autoregressive model are assumed to have a prior distribution. The prior distribution is combined with the likelihood function to obtain a posterior distribution. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…Thereafter, a multi-objective hybrid algorithm (MOHA), an extension of the self-adaptive hybrid algorithm is proposed and tested on the established multi-objective (MO) test functions. …”
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13
A new Gompertz-three-parameter-lindley distribution for modeling survival time data
Published 2025“…The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. …”
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Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft
Published 2015“…The developed stochastic algorithm has the capability to measure the parametric distribution function and validate the predict the reliability rate, mean time to failure and hazard rate. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The main contribution of this research is developing statistical approaches, and introducing new algorithms and resampling methods for analysing interval-censored data through AFT models.…”
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Slice sampler algorithm for generalized pareto distribution
Published 2018“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…In order to evaluate the scalability at specific data size the appropriate regression models are fitted through the measured data as functions of number of workers. …”
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Optimizing crystal size distribution based on different cooling strategies in batch crystallization process
Published 2024“…The crystallization process was developed and simulated in Matlab software using a potash alum in the water system. …”
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Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…A key property of our model is that the distributions of the observed count data are independent, conditional on the latent process, although the observations are correlated marginally. …”
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Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…To predict the output from the PV modules, 15 years of solar data were modeled with the aid of a beta probability density function. …”
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