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PREDICTION OF AVERAGE TEMPERATURE IN BANYUWANGI REGENCY USING SARIMA
Published 2025-07-01“…Predictions are made using the seasonal autoregressive integrated moving average (SARIMA) approach. …”
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Predicting waste generation using Bayesian model averaging
Published 2017-12-01“…Waste sampling, followed by a questionnaire survey, was carried out to gather data. The Bayesian model average method was used to identify factors significantly associated with waste generation. …”
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Reciprocal fraction function tools used for \-rung Quadripartitioned neutrosophic sets
Published 2025-05-01Get full text
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Solving Multi-Objective Complementary Programming Problem (MOCPP) by using Optimal Average
Published 2009-09-01Subjects: “…solving (mocpp) by using optimal average (oav)…”
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On Strong Convergence of Halpern’s Method Using Averaged Type Mappings
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Speech emotion recognition using long-term average spectrum
Published 2025-04-01“…In this work, a new framework for emotion recognition is proposed based on the long-term average spectrum (LTAS). Our framework is evaluated through a comparative study, where classifiers such as artificial neural network, K-nearest neighbours, logistic regression, Bayesian algorithms, tree-based logistics, and support vector machine were used. …”
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On the Analysis of Secrecy Outage Probability Using Average Channel Capacity
Published 2020-02-01“…We propose a novel approach using the average channel capacity of the primary channel and that of the eavesdropper channel to the outage probability of physically secure wireless signaling.…”
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Meta-analysis: on average, undergraduate students’ intelligence is merely average
Published 2024-04-01“…According to a widespread belief, the average IQ of university students is 115 to 130 IQ points, that is, substantially higher than the average IQ of the general population ( M = 100, SD = 15). …”
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Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of Things
Published 2013-12-01“…Bayesian model averaging is implemented by using Markov chain Monte Carlo approximation, and a novel dynamic Bayesian model averaging method is proposed based on event context clustering. …”
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Validation of Depth-Averaged Flow Model Using Flat-Bottomed Benchmark Problems
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Time Synchronization in Wireless Sensor Networks Using Max and Average Consensus Protocol
Published 2013-03-01“…This paper proposes a novel distributed time synchronization scheme for wireless sensor networks, which uses max consensus to compensate for clock drift and average consensus to compensate for clock offset. …”
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Analysis of some nonlinear deterministic oscillators using extended averaged equation approach
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PROJECTION OF THE INFLATION RATE IN PANGKALPINANG CITY USING THE AUTOREGRESSIVE MOVING AVERAGE (ARMA)
Published 2023-09-01“…The process projection is done using the Autoregressive Integrated Moving Average (ARIMA) model after passing the model fitting process first. …”
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Estimating the Prevalence of Opioid use Disorder in the Cincinnati Region using Probabilistic Multiplier Methods and Model Averaging
Published 2019-04-01“…# Background Opioid use disorder (OUD) and its consequences have strained the resources of health, social, and criminal justice services in the Cincinnati region. …”
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Quantifying volumes of volcanic deposits using time-averaged ASTER digital elevation models
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Using the Bayesian Model Averaging Approach for Genomic Selection by Considering Skewed Error Distributions
Published 2024-12-01“…In this study, we use the Bayesian model averaging (BMA) method for genomic selection by considering the skewed error distributions. …”
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Evaluating ESG efficiency using DEA an analysis of Dow Jones Industrial average companies
Published 2025-01-01“…For example, the Technology & Telecom, Financial Services, and Retail & Consumer Goods industries have efficiency scores calculated much higher using the input-oriented BCC approach (INBCC) compared to when the scores are derived from the CCR model. …”
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Identifying Cyclical Patterns of Behavior Using a Moving-Average, Data-Smoothing Manipulation
Published 2024-11-01“…However, identifying cyclical patterns of behavior can be difficult when using traditional methods of visual analysis. We describe a data-manipulation method, called data smoothing, in which one averages the data across time points within a specified window (e.g., 3, 5, or 7 days). …”
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