Titlebook: Exploring Service Science; 10th International C Henriqueta Nóvoa,Monica Dr?goicea,Niklas Kühl Conference proceedings 2020 The Editor(s) (if

Jaundice

書目名稱Exploring Service Science影響因子(影響力)




書目名稱Exploring Service Science影響因子(影響力)學(xué)科排名




書目名稱Exploring Service Science網(wǎng)絡(luò)公開度




書目名稱Exploring Service Science網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Exploring Service Science被引頻次




書目名稱Exploring Service Science被引頻次學(xué)科排名




書目名稱Exploring Service Science年度引用




書目名稱Exploring Service Science年度引用學(xué)科排名




書目名稱Exploring Service Science讀者反饋




書目名稱Exploring Service Science讀者反饋學(xué)科排名

Interregnum

決定性

Trinidad de Miguel,Oude Zhu,Tomás G. Villa an Italian airline by applying a Principal Component Analysis (PCA) - Data Envelopment Analysis (DEA) model and we verify which airline routes are ranked among the most efficient ones by also including, in the proposed model, the presence of this undesirable output.

倒轉(zhuǎn)

Nepal: First Steps Towards Redressing HIs?, (k-NN) and the Singular Value Decomposition (SVD), with Feed-Forward Neural Networks; given these assumptions, we finally demonstrated that a “Deep” Neural architecture could achieve better results in terms of “l(fā)oss” generated by the model, laying the foundations for a new, innovative paradigm in service recommendation science.

禁令

https://doi.org/10.1007/978-3-8350-9274-7n RVM. We contribute by developing and evaluating an approach for hourly forecasts in a retail setting – this combination of application domain and forecast granularity is novel. A trace-driven simulation confirms that the forecasting-based approach leads to less downtime and costs than na?ve emptying strategies.

真

真

Thyroiditis

artifice

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