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 40 for “"exponential smoothing"”.
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Complex exponential smoothing
Exponential smoothing is one of the most popular forecasting methods in practice. It has been used and researched for more than half a century. It started as an ad-hoc forecasting method and developed to a family of state-space models. Still all exponential smoothing methods are based on time …
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Application of exponential smoothing of forecasting sales of feed
Digitized by Kansas Correctional Industries
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Exponential Smoothing for Forecasting and Bayesian Validation of Computer Models
… series, we propose a new forecasting method, Exponential Smoothing with Covariates (ESCov). ESCov uses an ES method to model what left unexplained in a time series by covariates. We establish the optimality of ESCov, identify SSOE state space models underlying ESCov, and derive analytically …
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Optimizing smoothing parameters for the triple exponential forecasting model
Exponential smoothing has always been a popular topic of research in forecasting. The triple exponential smoothing in particular involves modeling a function that is a combination of level, trend and seasonal factors. While simulating the model, each of the factors is associated with a parameter …
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Development of dynamic recursive models for freeway travel time predictions
… of previous models, the base models including exponential smoothing model (ESM), moving average model (MAM), and Kalman filtering model (KFM) are developed to capture stochastic properties of traffic behavior for travel time prediction. By incorporating KFM into ESM and MAM, three dynamic …
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Field Evaluation Methodology for Quantifying Network-wide Efficiency, Energy, Emission, and Safety Impacts of Operational-level Transportation Projects
… also, investigates the ability of various data smoothing techniques to remove such erroneous data without significantly altering the underlying vehicle speed profile. Several smoothing techniques are then applied to the acceleration profile, including data trimming, Simple Exponential smoothing, …
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Detekce anomálií v množství generovaných záznamů o incidentech
… Predstavuje metódy STL decomposition, ARIMA, Exponential Smoothing a LSTM Networks. Cieľom je pomocou týchto metód vytvoriť algoritmus, ktorý dokáže analyzovať trend v množstve generovaných záznamov o incidentoch a detekovať anomálie z trendu. Riešenie bolo vytvorené na základe dátovej sady …
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A comparative study of different methods of predicting time series
… in this thesis are multiple regression, exponential smoothing, double exponential smoothing, Box-Jenkins method, and Winter's method. The second approach is using the concept of training neural nets and pattern recognition. This involves in designing a neural network and training it using …
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The evaluation of forecasting techniques as applied to housing starts
… such technique is obtained by using the simplest exponential smoothing model, that of single smoothing with a simple adaptive smoothing procedure, as described in this thesis.
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Forecasting international regional tourist arrivals to China
… forecast methods applied in this study are Holt, Exponential Smoothing, Naïve, ARMA, Neural, and Basic Structural Model (BSM) with and without intervention, and the causal explanatory forecast models are the Time-Varying Parameter (TVP) with and without dummy variables. This research has …
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Time series forecasting with recurrent neural networks
… world. Over the years, many models such as Exponential Smoothing and ARIMA are developed to make forecasts on time series. Recently, Recurrent Neural Networks (RNN) is gaining traction in the field of time series forecasting. RNN is a type of specialized neural network tailored towards …
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FORECASTING INTERMITTENT DEMAND FOR AIRCRAFT SPARE PARTS USING MACHINE LEARNING
… models, including Moving Average, Simple Exponential Smoothing, and Croston’s method as traditional time-series baselines, and gradient boosted decision trees (XGBoost), and artificial neural networks as machine learning models. Accuracy is assessed using MASE as the primary metric, …
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Mathematical Models of the Representation of Faces in Humans
… set forth, based on the statistical technique of exponential smoothing. In chapter 3 results of experiments testing this model are presented, demonstrating the model to be inadequate in certain respects. In particular a systematic bias towards the origin of face space is observed, a phenomenon …
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Optimization-based decision support system for retail souring
… updating methods for accuracy and found that an exponential smoothing-based model, modified to accommodate for changes in level few steps ahead, resulted in highest accuracy using Cumulative Absolute Percentage Error (CAPE). Next, we implemented a profit-maximizing optimization model to produce …
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A Multilayer Framework for Quality of Context in Context-Aware Systems
… as moving average (MA), weighted moving average, exponential smoothing, doubled exponential smoothing, and autoregressive moving average (ARMA).
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Forecasting the S&P 500 index using time series analysis and simulation methods
… Integrated Moving Averages (ARIMA), Double Exponential Smoothing, Neural Networks, GARCH, and Bootstrapping Simulations. The criteria to evaluate forecasts were the following metrics for the evaluation range: Root Mean Square Error (RMSE), Absolute Error (MAE), Akaike information criterion …
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Forecasting and inventory control for hospital management
… forecasting methods, including moving averages, exponentially smoothed averages and the Box-Jenkins method. Comparisons were made in terms of relative size of forecast errors; ease of data maintenance, and demands upon hospital clerical staffs. The computer system: BRUFICH facilitated scrutiny of …
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Forecasting demand for district heating using different forecasting methods
… created, LOWESS or Locally Weighted Scatter-plot Smoothing. LOWESS offers a non-linear correlation by giving more weight to values closer to the observation. The third model was an exponential smoothing model, the Holt-Winters method, a model that offers to take into account trend and seasonality. …
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Exchange rate forecasting: regional applications to ASEAN, CACM, MERCOSUR and SADC countries
… crisis, especially in Asia and Latin America. Exponential smoothing time series models provided the most accurate forecasts for the sampled exchange rates, while combination models outperformed single time series models in about 70% of the cases. ARDL cointegration models had limited success in …
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Autoscaling through Self-Adaptation Approach in Cloud Infrastructure. A Hybrid Elasticity Management Framework Based Upon MAPE (Monitoring-Analysis-Planning-Execution) Loop, to Ensure Desired Service Level Objectives (SLOs)
… time series analysis (moving average method / exponential smoothing) and threshold based static rules (with multiple monitoring intervals and dual threshold settings) during analysis and planning phases of MAPE loop, respectively. Mathematical illustration of the framework incorporates multiple …
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