|
|
|
|
|
Dean Fantazzini, Julia Pushchelenko, Alexey Mironenkov and Alexey Kurbatskii
This paper examines the suitability of Google Trends data for the modeling and forecasting of interregional migration in Russia. Monthly migration data, search volume data, and macro variables are used with a set of univariate and multivariate models to ...
ver más
|
|
|
|
|
|
|
|
|
Dakotah Hogan, John Elshaw, Clay Koschnick, Jonathan Ritschel, Adedeji Badiru and Shawn Valentine
Traditional learning curve theory assumes a constant learning rate regardless of the number of units produced. However, a collection of theoretical and empirical evidence indicates that learning rates decrease as more units are produced in some cases. Th...
ver más
|
|
|
|
|
|
|
|
|
Marcos Álvarez-Díaz, Manuel González-Gómez and María Soledad Otero-Giráldez
This study explores the forecasting ability of two powerful non-linear computational methods: artificial neural networks and genetic programming. We use as a case of study the monthly international tourism demand in Spain, approximated by the number of t...
ver más
|
|
|
|
|
|
|
|
|
Syed Ale Raza Shah, Mr, Sofia Anwar, Prof., Syed Asif Ali Naqvi, Dr
Pág. 348 - 369
Over the last decade, the importance of energy consumption in transport sector has burgeoned forth and has been growing rapidly in Pakistan, and the course is being augured to linger over the coming decades. This paper brings about the function of transp...
ver más
|
|
|
|
|
|
|
|
|
Aytaç PEKMEZCI, Nevin Güler DINÇER, Öznur ISÇI GÜNERI
Pág. 307 - 320
Fuzzy Time Series (FTS) methods are used frequently in time series analysis due to their advantages such as having no assumptions, having few observations, being able to process incomplete, uncertain and linguistic data. The FTS consists of 6 steps, each...
ver más
|
|
|
|