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You searched for subject:(Power predictions). Showing records 1 – 4 of 4 total matches.

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1. Hildén, Johannes. Predicting power consumption of shared electric vehicles using regression and cluster analysis .

Degree: Chalmers tekniska högskola / Institutionen för data och informationsvetenskap, 2019, Chalmers University of Technology

 When planing a trip with an electric vehicle, one has to predict how much power will be consumed in advance in order not to risk… (more)

Subjects/Keywords: Regression; Clustering; Cluster based regression; Electric vehicles; Predictions; Power consumption; Car-sharing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hildén, J. (2019). Predicting power consumption of shared electric vehicles using regression and cluster analysis . (Thesis). Chalmers University of Technology. Retrieved from http://hdl.handle.net/20.500.12380/300039

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hildén, Johannes. “Predicting power consumption of shared electric vehicles using regression and cluster analysis .” 2019. Thesis, Chalmers University of Technology. Accessed September 23, 2019. http://hdl.handle.net/20.500.12380/300039.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hildén, Johannes. “Predicting power consumption of shared electric vehicles using regression and cluster analysis .” 2019. Web. 23 Sep 2019.

Vancouver:

Hildén J. Predicting power consumption of shared electric vehicles using regression and cluster analysis . [Internet] [Thesis]. Chalmers University of Technology; 2019. [cited 2019 Sep 23]. Available from: http://hdl.handle.net/20.500.12380/300039.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hildén J. Predicting power consumption of shared electric vehicles using regression and cluster analysis . [Thesis]. Chalmers University of Technology; 2019. Available from: http://hdl.handle.net/20.500.12380/300039

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Texas – Austin

2. Srour, Malek. Data-dependent cycle-accurate power modeling of RTL-level IPs using machine learning.

Degree: MSin Engineering, Electrical and Computer Engineering, 2018, University of Texas – Austin

 In a chip design project, early design planning has a strong impact on the schedule and the cost of design. Power estimation is part of… (more)

Subjects/Keywords: Cycle-accurate power modeling; Power modeling; Machine learning; Chip design; Power estimation; Register transfer level; Abstraction level; Power predictions; Cycle-specific models

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Srour, M. (2018). Data-dependent cycle-accurate power modeling of RTL-level IPs using machine learning. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/65980

Chicago Manual of Style (16th Edition):

Srour, Malek. “Data-dependent cycle-accurate power modeling of RTL-level IPs using machine learning.” 2018. Masters Thesis, University of Texas – Austin. Accessed September 23, 2019. http://hdl.handle.net/2152/65980.

MLA Handbook (7th Edition):

Srour, Malek. “Data-dependent cycle-accurate power modeling of RTL-level IPs using machine learning.” 2018. Web. 23 Sep 2019.

Vancouver:

Srour M. Data-dependent cycle-accurate power modeling of RTL-level IPs using machine learning. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2019 Sep 23]. Available from: http://hdl.handle.net/2152/65980.

Council of Science Editors:

Srour M. Data-dependent cycle-accurate power modeling of RTL-level IPs using machine learning. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/65980


Loughborough University

3. Kossmann de Menezes, Anna Carolina. Improving predictions of operational energy performance through better estimates of small power consumption.

Degree: Thesis (Eng.D.), 2013, Loughborough University

 This Engineering Doctorate aims to understand the factors that generate variability in small power consumption in commercial office buildings in order to generate more representative,… (more)

Subjects/Keywords: Buildings; Performance gap; Energy performance; Operational performance; Predictions; Offices; Small power; Plug loads; Appliances; Electricity consumption; Occupant behaviour

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kossmann de Menezes, A. C. (2013). Improving predictions of operational energy performance through better estimates of small power consumption. (Doctoral Dissertation). Loughborough University. Retrieved from https://dspace.lboro.ac.uk/2134/13549 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763407

Chicago Manual of Style (16th Edition):

Kossmann de Menezes, Anna Carolina. “Improving predictions of operational energy performance through better estimates of small power consumption.” 2013. Doctoral Dissertation, Loughborough University. Accessed September 23, 2019. https://dspace.lboro.ac.uk/2134/13549 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763407.

MLA Handbook (7th Edition):

Kossmann de Menezes, Anna Carolina. “Improving predictions of operational energy performance through better estimates of small power consumption.” 2013. Web. 23 Sep 2019.

Vancouver:

Kossmann de Menezes AC. Improving predictions of operational energy performance through better estimates of small power consumption. [Internet] [Doctoral dissertation]. Loughborough University; 2013. [cited 2019 Sep 23]. Available from: https://dspace.lboro.ac.uk/2134/13549 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763407.

Council of Science Editors:

Kossmann de Menezes AC. Improving predictions of operational energy performance through better estimates of small power consumption. [Doctoral Dissertation]. Loughborough University; 2013. Available from: https://dspace.lboro.ac.uk/2134/13549 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763407

4. Σιδεράτος, Γεώργιος. Ανάπτυξη μοντέλων πρόβλεψης παραγωγής αιολικής ισχύος με χρήση νευρωνικών δικτύων και τεχνικών ασαφούς λογικής.

Degree: 2010, National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ)

Subjects/Keywords: Πρόβλεψη αιολικής ισχύος; Νευρωνικά δίκτυα ακτινωτής βάσης; Αυτό-οργανούμενος χάρτης; Ασαφής λογική; Αβεβαιότητα πρόβλεψης; Πιθανοτική πρόβλεψη; Αριθμητικές προβλέψεις καιρού; Wind power forecasting; RBF neural networks; Self-organized map; Fuzzy logic; Prediction uncertainty; Probabilistic wind power prediction; Numerical whether predictions

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Σιδεράτος, . . (2010). Ανάπτυξη μοντέλων πρόβλεψης παραγωγής αιολικής ισχύος με χρήση νευρωνικών δικτύων και τεχνικών ασαφούς λογικής. (Thesis). National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ). Retrieved from http://hdl.handle.net/10442/hedi/21037

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Σιδεράτος, Γεώργιος. “Ανάπτυξη μοντέλων πρόβλεψης παραγωγής αιολικής ισχύος με χρήση νευρωνικών δικτύων και τεχνικών ασαφούς λογικής.” 2010. Thesis, National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ). Accessed September 23, 2019. http://hdl.handle.net/10442/hedi/21037.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Σιδεράτος, Γεώργιος. “Ανάπτυξη μοντέλων πρόβλεψης παραγωγής αιολικής ισχύος με χρήση νευρωνικών δικτύων και τεχνικών ασαφούς λογικής.” 2010. Web. 23 Sep 2019.

Vancouver:

Σιδεράτος . Ανάπτυξη μοντέλων πρόβλεψης παραγωγής αιολικής ισχύος με χρήση νευρωνικών δικτύων και τεχνικών ασαφούς λογικής. [Internet] [Thesis]. National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ); 2010. [cited 2019 Sep 23]. Available from: http://hdl.handle.net/10442/hedi/21037.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Σιδεράτος . Ανάπτυξη μοντέλων πρόβλεψης παραγωγής αιολικής ισχύος με χρήση νευρωνικών δικτύων και τεχνικών ασαφούς λογικής. [Thesis]. National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ); 2010. Available from: http://hdl.handle.net/10442/hedi/21037

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.