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1
Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting
Published 2024“…However, convolutional neural networks may suffer from overfitting, particularly in cases in which the structure of the time series is overly simplified. Using Bayesian neural networks, we modeled network weights and biases as probability distributions to assess aleatoric and epistemic variability, employing Markov chain Monte Carlo and bootstrap resampling techniques. …”
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2
Population genetic structure of Malayan Tapir (Tapirus indicus Desmarest) in Peninsular Malaysia
Published 2019“…Using K-means clustering algorithm, five clusters were inferred among the wild samples (N = 57), which showed a complex population structure probably comprising multiple continuous populations that also experiencing considerably restricted gene flow due to isolation by geographical barriers especially mountain ranges. …”
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3
Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
4
Agents for Fuzzy Indices of Reliability Power System with Uncertainty Using Monte Carlo Algorithm
Published 2014“…Two agents are developed based on fuzzy parameters of Monte Carlo i.e. current with its means and variances; the other agent is the probability of outage capacity for each state. …”
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5
Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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6
Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…Directional statistics is a branch of statistics which deal with the data in angle form in which the method of analysis is different from linear data. For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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7
An improvement on the valiantbrebner hypercube data broadcasting technique / Nasaruddin Zenon
Published 1990“…The writer tries to improve this algorithm because it is the only known algorithm for the hypercube machine that has the probability of more than i (log n) processors will simultaneously try to transmit a message through a given processor decreases exponentially with i. …”
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8
Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm
Published 2023Article -
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…In recent years, photovoltaic distributed generation (PVDG) has seen rapid growth due to its benefits in supporting the power system network, enhancing the transmission and distribution of power, and minimizing power congestion. …”
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10
Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Two selection methods that are used in Genetic Algorithm are the roulette wheel and tournament selections. …”
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11
A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…GDP forecasting is aided by the genetic algorithm radial basis neural network, which allows the government to make timely and effective macrocontrol plans based on the forecast trend of GDP in the region. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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13
REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC
Published 2011“…The partitioning allows allocation of appropriate DVC coding parameters (virtual channel, rate, and quantizer) to each region. The resulting regions map is compressed by employing quadtree algorithm and communicated to the encoder via the feedback channel. …”
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14
A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…In particular, the regional quantile estimates can provide a more accurate estimation compared to at-site quantile estimates using an appropriate statistical distribution.…”
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15
A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…In particular, the regional quantile estimates can provide a more accurate estimation compared to at-site quantile estimates using an appropriate statistical distribution.…”
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16
Novel wide-area fault location and predictive maintenance technique for distribution system
Published 2023“…This paper presents a reliable, automated fault location algorithm within a wide-area distribution network using a limited number of monitoring devices. …”
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Clustering of Indonesian forest fires using self organizing maps
Published 2006“…We analyze the distributions of the hot spots locations of the regions that may have the high frequencies to risk of the forest fires disaster using the SOM algorithm. …”
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Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…Although the number of these target-like data is small, they may cause false alarm and perturb the target detection. K-distribution is known as the best fit probability density function for the radar sea clutter. …”
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19
Communication and computational cost on parallel algorithm of PDE elliptic type
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20
A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…In particular, the regional quantile estimates can provide a more accurate estimation compared to at-site quantile estimates using an appropriate statistical distribution.…”
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