Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 28 for “"SARIMA"”.
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New product forecasting of appliance and consumables : SARIMA model
… paper focuses on an operational level model, SARIMA, which is a time series analysis that considers seasonality and has high accuracy in forecasting. The SARIMA model is implemented with grid search in Python via a demand planning tool, which saves client's time. Weighted consumption rate will …
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Outlier treatments using interolation on Malaysia tourist arrival forecasting: SARIMA and ANN approaches
… Spline Interpolation methods. In this study, SARIMA model and Artificial Neural Network model were used as forecasting tools using the data before and after outlier treatment. The comparison of forecast performance between all models were calculated using MSE, MAD, MAPE and R2 including the …
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Comparação entre os Modelos SARIMA e os Métodos de Machine Learning para previsão de demanda
… LSTM, em relação aos modelos de Séries Temporais SARIMA, aplicado a 84 séries temporais de produtos reais, para realizar previsão de demanda. Considerando como medida de erro o MAPE, ambos métodos de Aprendizado de Máquinas tiveram uma performance melhor que os modelos SARIMA, porém o método que …
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Type-2 Fuzzy Probabilistic System for Proactive Monitoring of Uncertain Data-intensive Seasonal Time Series
… fuzzy sets. A special case study, a type-2 fuzzy SARIMA system is proposed and experimented in forecasting singleton and uncertain non-singleton bench mark data - Mackey-Glass time series. The results show that the type-2 fuzzy SARIMA system has achieved significant improvements beyond its …
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Type-2 Fuzzy Probabilistic System for Proactive Monitoring of Uncertain Data-intensive Seasonal Time Series
… fuzzy sets. A special case study, a type-2 fuzzy SARIMA system is proposed and experimented in forecasting singleton and uncertain non-singleton bench mark data - Mackey-Glass time series. The results show that the type-2 fuzzy SARIMA system has achieved significant improvements beyond its …
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SARIMA Short to Medium-Term Forecasting and Stochastic Simulation of Streamflow, Water Levels and Sediments Time Series from the HYDAT Database
… Autoregressive Integrated Moving Average (SARIMA) time series models. The methodology can account for linear trends in the time series that may result from climate and environmental changes. A Universal Canadian forecast Application using python web interface was developed to generate …
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Predicción de la demanda de pasajeros a clústeres de estaciones del Metropolitano usando métodos de Data Mining, la metodología Box-Jenkins y Sarima
… the passenger demand of station clusters using SARIMA from a spatio-temporal analysis using two data mining methods and the Box-Jenkins methodology to get the best possible model for cluster. The results of the spatio-temporal analysis showed similar behavior between stations when grouped into …
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Forecasting pelagic fish in Malaysia using ets state space approach
… collected data for the period 2007 – 2011. The SARIMA(1,1,1)(0,0,1)[12], SARIMA(1,1,4)(0,0,1)[12], SARIMA(2,1,1)(0,0,1)[12] and ETS (M, A, M), ETS (M, N, M), ETS (M, A, M) for Dussumiera acuta (tamban buloh), Rastrelliger kanagurta (kembong) and Thunnus tonggol (Tongkol hitam) were proposed …
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An Exploratory Study on Methods for Interpolating and Extrapolating Baseball Win-Loss Percentage
… Auto-Regressive Integrated Moving Average (SARIMA) model that was generated following the Box-Jenkins method. With W-L% data from 1998 to 2021, we produce Fourier series, cubic spline, and SARIMA models for each team with the help of Python. The Fourier series and cubic spline model were …
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Influenza Modeling, New York City, January 2000 to March 2010
… Autoregressive Integrated Moving Average (SARIMA), and General Additive Modeling (GAM) statistical modeling techniques to find the optimal modeling technique for ILI visits from January 2002 to June 2007. The optimal modeling technique was then used to validate forecasts from July 2007 to …
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Effects of a global pandemic on the collection and disposal of municipal solid waste
… virus. As such, in the first part of the study, SARIMA models were developed to predict residential waste collection rates (RWCR) across four North American jurisdictions before and during the pandemic. Unlike waste disposal rates, RWCR is relatively less sensitive to the changes in COVID-19 …
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Previsões do PIB brasileiro a partir de informações de mercado: aplicações com dados de diferentes frequências
… previsão dos modelos utilizados (MIDAS, ARIMA e SARIMA). A partir das hipóteses de mercados eficientes e de expectativas racionais, é possível esperar que as informações contidas nos preços dos ativos do mercado financeiro são suficientes para gerar previsões para o PIB brasileiro, melhores do …
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From Seasonality to Causality: Understanding Urban Water Usage Using Statistical and Machine Learning Models
… Autoregressive Integrated Moving Average (SARIMA) and Long Short-Term Memory (LSTM) model to identify seasonal trends and assess predictive power in water usage. Results indicate a steady decline in overall water usage since 2020. Geographic location also plays a role in determining water …
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Responding to traveling patients' seasonal demands for health care services in the Veterans Health Administration
… autoregressive integrated moving average (SARIMA) models to help the clinic better forecast demand for its services by traveling Veterans. Our models were able to project demand, in terms of encounters and unique patients, with significantly less error than the traditional historical …
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On Development and Performance Evaluation of Some Biosurveillance Methods
… autoregressive integrated moving average (SARIMA) based surveillance chart, and compares it with the CDC Early Aberration Reporting System (EARS) W2c method using both authentic and simulated data. After successfully removing the long-term trend and the seasonality involved in syndromic …
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Neural Decomposition of Time-Series Data for Effective Generalization
… forecasting techniques including ARIMA, SARIMA, SVR with a radial basis function, Gashler and Ashmore’s model, and echo state networks.</p>
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Desarrollo e implementación de un sistema automatizado de pronóstico de demanda dentro del sector de la venta de neumáticos
… metodologías de pronóstico: Media Móvil, ARIMA, SARIMA, Prophet y XGBoost. Estos modelos serán evaluados para determinar su eficacia en la predicción de la demanda en el contexto específico de la empresa. El propósito es ofrecer una herramienta que no solo aumente la precisión de los pronósticos, …
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Modeling and prediction of wind power data
… to predict wind power, including ARIMA model, SARIMA model, ARAR model, Holt-Winters method, and a state-space model. We compared the difference between the predicted data and the original data. We conclude that a state space model incorporating trend and seasonal variables, a Kalman prediction …
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Time Series Analysis of Fine Particulates Matter (PM2.5) in Chaoyang District of Beijing
… and using the Box-Jenkins method to build a SARIMA model (Seasonal Autoregressive Integrated Moving Average). The results showed the PM2.5 concentration decreased from 2010 to 2012. The 24-hour PM2.5 concentration was 294μg/m³, ranged from 265.2μg/m³ to 318.5μg/m³. And the annual PM2.5 …
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Space-time statistical analysis of malaria morbidity incidence cases in Ghana: A geostatistical modelling approach
… autoregressive integrated moving average (SARIMA) predictive models have been studied and applied to the monthly malaria morbidity cases from both district and regional health facilities in Ghana. The study sought to explore the spatio-temporal distributions of the malaria morbidity …
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