[PDF] Top 20 Forecasting telecommunications data with linear models
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Forecasting telecommunications data with linear models
... Note: RT is the robust trend model; ARIMA is the autoregressive integrated moving average model; HOLT is Holt’s linear no trend model; Holt-D is Holt’s model with exponential smoothing; [r] ... See full document
28
A hybrid model for short term real-time electricity price forecasting in smart grid
... input data in views of linear behavior, non-linear behav- ior and errors optimization within the ...with forecasting tasks based on insufficient data compared with the traditional ... See full document
14
Review on Weather Forecasting using Linear Regression and SVM in Big Data
... Climate forecasting is very much considered as the most requesting issue both hypothetically and experimentally by the world in the most recent ...creating models which help towards a viable forecast of the ... See full document
5
Statistical Modeling for Rice Production in Pakistan
... time-series data for the period 1981-82 to 2015-16 on production of rice in ...For forecasting purpose, different linear and non-linear growth models such as Linear trend model, ... See full document
7
Forecasting International Tourism Demand- An Empirical Case in Taiwan
... relevant data and the inherent characteristic of a time series, in this paper, we consider possible forecasting models established under linear regression, autoregressive integrated moving ... See full document
14
Exchange Rate Forecasting Using Non-linear Threshold Models
... with data from record of Central Bank of Nigeria through their official ...threshold models in forecasting the exchange rate of Nigeria in relation to United States of American dollar as bench ... See full document
7
Forecasting Stock Prices With Linear And Nonlinear Settings: A Comparison
... Although, linear models are considered a good estimation technique to study time series processes, it is important to test the non-linearity and non-gaussianity of the ...the data may contain useful ... See full document
10
Escalation of Forecasting Accuracy through Linear Combiners of Predictive Models
... the data points belong to one category fall on one side and data points belong to other class fall on the other ...both linear & non-linear classification using different kernel functions ... See full document
14
Time Series Forecasting of Hourly PM10 Using Localized Linear Models
... localized linear models for forecasting hourly PM10 concentration values using data from the monitoring networks of the cities of Athens, Helsinki and ...examined data set and ... See full document
10
Forecasting Industrial Production in Iran: A Comparative Study of Artificial Neural Networks and Adaptive Nero-Fuzzy Inference System
... classic models (Chen & Chen, 2015). In these models, it is assumed that expression of a behavioral pattern by the historical data can be achieved by models with high explanatory power ... See full document
16
Linear and Neural Network-based Models for Short-Term Heat Load Forecasting
... short-term forecasting of heat load in a district heating system of Ljubljana is ...load data and weather-related influential variables for five subsequent winter seasons of district heating operation are ... See full document
8
Bank Net Interest Margin Forecasting and Capital Adequacy Stress Testing by Machine Learning Techniques
... the forecasting models from regulators and ...using linear regression models which fore- cast the banking-industry incomes measured by Aggregate Net Interest ...NIM forecasting at an ... See full document
52
Forecasting U S output growth with non linear models in the presence of data uncertainty
... of data mis-measurement on the parameter estimates and in the data the forecasts were conditioned on, in the case of 1-step forecasting, but was primarily due to errors in the data being ... See full document
28
Improving the performance of financial forecasting using different combination architectures of ARIMA and ANN models
... individual forecasting models that have been proposed in the literature, accurate forecasting is yet one of the major challenging problems facing decision makers in various fields, especially ... See full document
18
Econometric forecasting of financial assets using non linear smooth transition autoregressive models
... non-linear models emerged from empirical observations of financial markets and the inability of linear models to explain some frequently occurring phenomena in financial ...financial ... See full document
344
Are CDS spreads predictable? An analysis of linear and non linear forecasting models
... Another study which is similar to Alexander and Kaeck (2008) and is based on the analysis of the iTraxx Europe CDS index is Byström (2006). The former study used a Markov switching regression model to explain changes in ... See full document
26
Forecasting Inflation using Functional Time Series Analysis
... functional data can also be an input output system, it can also be used in linear ...a data using functional data ...to data means estimating its parameters , which determines its ... See full document
28
Forecasting nitrate concentration in groundwater using artificial neural network and linear regression models
... Artificial neural networks (ANNs) are able to approximate accurately complicated non-linear input-output relationships. The ANN is used as an approximation tool rather than a com- plex mathematical calculation, ... See full document
6
Generalized linear mixed models for count data
... Theoretically, the EM algorithm is the most accurate method that we have dis- cussed so far. Unlike the Laplace approximation and Gauss-Hermite quadrature, where we have to worry about the coefficients of the error terms ... See full document
97
Financial analysis considering distress prediction models of telecommunications companies listed in Athens Stock Exchange: Hellenic Telecommunications Organization, Forthnet, Hellas Online
... listed telecommunications companies and the related market in ...mobile telecommunications market and utilizing its expertise and resources to invest to developing markets in ...the ... See full document
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