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Könyv Enhanced Bayesian Network Models for Spatial Time Series Prediction Monidipa Das

Enhanced Bayesian Network Models for Spatial Time Series Prediction

Recent Research Trend in Data-Driven Predictive Analytics

Szerző: Monidipa Das, Soumya K. Ghosh
Nyelv: Angol
Kötés: Kemény kötésű
Kiadó: Springer Nature Switzerland AG
Elérhetőség: Beszállítói készleten
Küldés 10-13 napon belül
58 426 Ft
This research monograph is highly contextual in the present era of spatial/spatio-temporal data expl...

Információk a könyvről

Szerző
Monidipa Das, Soumya K. Ghosh
Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2019
oldal
149
EAN
9783030277482
Enbook ID
24519323
Kiadó
Springer Nature Switzerland AG
Súly
454
Méretek
155 x 235 x 15

Teljes leírás

This research monograph is highly contextual in the present era of spatial/spatio-temporal data explosion. The overall text contains many interesting results that are worth applying in practice, while it is also a source of intriguing and motivating questions for advanced research on spatial data science. The monograph is primarily prepared for graduate students of Computer Science, who wish to employ probabilistic graphical models, especially Bayesian networks (BNs), for applied research on spatial/spatio-temporal data. Students of any other discipline of engineering, science, and technology, will also find this monograph useful. Research students looking for a suitable problem for their MS or PhD thesis will also find this monograph beneficial. The open research problems as discussed with sufficient references in Chapter-8 and Chapter-9 can immensely help graduate researchers to identify topics of their own choice. The various illustrations and proofs presented throughout the monograph may help them to better understand the working principles of the models. The present monograph, containing sufficient description of the parameter learning and inference generation process for each enhanced BN model, can also serve as an algorithmic cookbook for the relevant system developers.

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