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Enhanced predictive modelling process of broadband services adoption based on time series data


Križanović, Višnja; Žagar, Drago; Grgić, Krešimir; Vranješ, Mario
Enhanced predictive modelling process of broadband services adoption based on time series data // Advanced engineering informatics, 38 (2018), October 2018; 142-167 doi:10.1016/j.aei.2018.06.003 (međunarodna recenzija, članak, znanstveni)


Naslov
Enhanced predictive modelling process of broadband services adoption based on time series data

Autori
Križanović, Višnja ; Žagar, Drago ; Grgić, Krešimir ; Vranješ, Mario

Izvornik
Advanced engineering informatics (1474-0346) 38 (2018), October 2018; 142-167

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Broadband services ; Broadband adoption ; Predictive modelling

Sažetak
In this paper, the importance of the predictive modelling process of broadband services adoption is described. A detailed overview of different analytical models used for prediction, i.e., fitting and forecasting processes of broadband services adoption are presented. Furthermore, a comparison of several analytical models commonly used for prediction of broadband adoption is conducted. In order to more accurately fit to the existing broadband adoption time series data, and to forecast the future broadband services adoption paths, the features of the most accurate common predictive models have been identified for different phases of broadband services adoption. Considering the given results, usage of additional models in the predictive modelling process is analyzed. The objective of these analyses is set to improve the accuracy of the existing predictive modelling process. The accuracy of the predictive modelling process using additional models is tested and compared in different phases of broadband adoption. The model which gives the most accurate results is identified. Finally, in order to enable the usage of this model within a whole broadband service life cycle, as well as to include a greater number of explanatory parameters in predictive modelling process, an enhanced predictive modelling process is proposed.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Ustanove
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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