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.
Results
Showing 1 to 20 of 132 for “"forecasting models"”.
-
A Comparison of Corn Yield Forecasting Models
… to compare and analyze several different yield forecasting methods. The study analyzes corn yields in Ohio and South Dakota for the years 1986 through 2012. A base model, with a trend and state dummy variable is developed. Two competing models, one with objective variables and one with …
-
A Comparison of Corn Yield Forecasting Models
… to compare and analyze several different yield forecasting methods. The study analyzes corn yields in Ohio and South Dakota for the years 1986 through 2012. A base model, with a trend and state dummy variable is developed. Two competing models, one with objective variables and one with …
-
Deep Learning-based Time Series Forecasting: Models and Applications
… of complex data, time series modeling and forecasting have always been hot topics. In the big data environment, time series often have the characteristics of multi-source complexity, dynamic heterogeneity, uncertainty, and nonlinearity, which brings tremendous challenges to the processing …
-
Alternative Forecasting Models for Farm Wheel Tractor Horsepower Purchases
… Very little attention has been devoted to forecasting tractor demand.
-
One, two and three quarter forecasting models for broiler price
… of this study was to develop easy to use price forecasting models to predict broiler price one, two and three quarters in advance. A system of five equations was developed for the two and three quarter lag models and a system of four equations was developed for the one quarter lag model. All …
-
Structure combination of forecasting models with application in the energy sector
… networks and seasonal exponential smoothing models using synthetic data and real time series, from the electricity sector. It starts with a literature review on combining forecasts and ensembles of neural networks, and highlights their use in forecasting within the energy sector. Research …
-
A Comparison of Natural Gas Spot Price Linear Regression Forecasting Models
… This paper examines a natural gas price forecasting model developed by the U.S. Department of Energy, Energy Information Agency (EIA). This paper proposes that a more accurate forecasting model can be created from the EIA model by focusing on forecasting price during only the winter …
-
Value chain diversification in the sugar industry using quantitative economic forecasting models
… for model building. Seven different types of models were considered, including the Naïve method, simple and weighted moving averages, simple exponential smoothing, Holt's method, Holt-Winters' method and Auto-Regressive Integrated Moving Average (ARIMA) models. Each type of model was analysed …
-
Graphon Mean Field Games with Finite States and Forecasting Models for the Energy Market
… with applied contributions to the modelling and forecasting of renewable energy systems. The first part, carried out in collaboration with Prof. Francesco Giuseppe Cordoni, focuses on the mathematical analysis of graphon mean field games (GMFGs), a generalisation of classical MFGs that allows for …
-
Development of Remote Sensing Assisted Water Quality Nowcasting and Forecasting Models for Coastal Beaches
… in this dissertation for nowcasting and forecasting recreational water quality of Holly Beach in Louisiana, USA. The modeling framework is composed of four models/systems: (1) an Artificial Neural Network (ANN) model (Model 1) and an US EPA Virtual Beach (VB) Program-based model for …
-
General Aviation Demand Forecasting Models and a Microscopic North Atlantic Air Traffic Simulation Model
… first topic is the General Aviation (GA) demand forecasting models. The contributions to this topic are three fold: 1) we calibrated an econometric model to investigate the impact of fuel price on the utilization rate of GA piston engine aircraft, 2) we adopted a logistic model to identify the …
-
INTEGRATING FUNGICIDE RESISTANCE MONITORING AND FORECASTING MODELS FOR THE PRECISION MANAGEMENT OF GRAPEVINE DOWNY MILDEW
… selection pressure. In this framework, disease forecasting models and resistance monitoring represent key tools to support rational decision-making and optimise fungicide use by aligning chemical interventions with actual infection risk. The aim of this PhD thesis was to improve the management …
-
Orphan drugs : future viability of current forecasting models, in light of impending changes to influential market factors
… to establish a baseline for how orphan drug forecasting is currently undertaken by financial market and industry analysts with the intention of understanding the variables typically accounted for in such a model. A literature search formed the basis of subsequent interviews conducted with …
-
Artificial Neural Network-Based Flood Forecasting: Input Variable Selection and Peak Flow Prediction Accuracy
… and costly natural disaster in Canada. Flow forecasting models can be used to provide an advance warning of flood risk and mitigate flood damage. Data-driven models have proven to be suitable for flow forecasting applications, yet there are several outstanding challenges associated with model …
-
Forecasting international movements of Returnable Transport Items
… and Canada by developing a one-month-ahead forecasting model to predict the net monthly international flows. To develop the model, six years of historical time series data was decomposed into key elements: level, trend, and seasonality. The results of the decomposition method were used to …
-
My4Sight: A Human Computation Platform for Improving Flu Predictions
… for harnessing human insights in improving forecasting models for infectious diseases, such as Influenza and Ebola. In this thesis, we present the design and implementation of My4Sight, a human computation system developed to harness human insights and intelligence to improve forecasting …
-
Forecast-Driven Inventory Management for the Fast-Moving Consumer Goods Industry
… the development and evaluation of various demand forecasting models for the Fast-Moving Consumer Goods (FMCG) industry on real-world data to devise an inventory control policy for a third-party logistics provider. Demand forecasting is crucial in the retail industry, influencing supply chain …
-
Fuzzy time series analysis and prediction using swarm optimized hybrid model.
Time series forecasting has an extensive trajectory record in the fields of business, economics, energy, population dynamics, tourism, etc. where factor models, neural network models, Bayesian models are exceedingly applied for effective prediction. It has been exemplified in numerous forecasting …
Page 1 of 7