MARC details
000 -LEADER |
fixed length control field |
02622cam a2200313 a 4500 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
EG-GiCUC |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
210624s2021 ua d f m 000 0 eng d |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
EG-GiCUC |
Language of cataloging |
eng |
Transcribing agency |
EG-GiCUC |
041 0# - LANGUAGE CODE |
Language code of text/sound track or separate title |
eng |
049 ## - LOCAL HOLDINGS (OCLC) |
Holding library |
Deposite |
097 ## - Thesis Degree |
Thesis Level |
M.Sc |
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) |
Classification number |
Cai01.18.04.M.Sc.2021.Do.B |
100 0# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Doaa Mahmoud Mohamed Abdelaty |
245 10 - TITLE STATEMENT |
Title |
Big data analysis using intelligent statistical techniques / |
Statement of responsibility, etc. |
Doaa Mahmoud Mohamed Abdelaty ; Supervised Elhousainy Abdelbar Rady , Amal Mohamed Abdelfattah |
246 15 - VARYING FORM OF TITLE |
Title proper/short title |
تحليل البيانات الكبيرة بإستخدام التقنيات الإحصائية الذكية |
260 ## - PUBLICATION, DISTRIBUTION, ETC. |
Place of publication, distribution, etc. |
Cairo : |
Name of publisher, distributor, etc. |
Doaa Mahmoud Mohamed Abdelaty , |
Date of publication, distribution, etc. |
2021 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
89 P . : |
Other physical details |
charts ; |
Dimensions |
30cm |
502 ## - DISSERTATION NOTE |
Dissertation note |
Thesis (M.Sc.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Statistics and Econometrics |
520 ## - SUMMARY, ETC. |
Summary, etc. |
In the era of big data, we surrounded when in huge amounts of devices (Home Appliances) which use a very amount of electricity and this effect the community . Given the rise of smart electricity meters and the wide adoption of electricity generation technology, there is a wealth of electricity usage data available. So, The big data framework applied to smart meters offers an exception platform for data-driven forecasting and decision-making to achieve sustainable energy efficiency. The key elements for understanding and predicting household energy consumption are activities occupants perform, by clustering using of Appliances with Appliances, and Appliances with time. Appliances and the times that appliances are used, and inter-appliance dependencies. This information can be extracted from the context rich big data from smart meters. Although this is challenging because it is not trivial to mine complex interdependencies between appliances from multiple concurrent data streams, it is difficult to derive accurate relationships between interval-based events, where multiple appliance usage persists, and continuous generation of the energy consumption data can trigger changes in appliance associations with time and appliances. And This data represents a multivariate time series of power related variables, that in turn could be used to model and even forecast future electricity consumption |
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE |
Additional physical form available note |
Issued also as CD |
653 #4 - INDEX TERM--UNCONTROLLED |
Uncontrolled term |
Big Data |
653 #4 - INDEX TERM--UNCONTROLLED |
Uncontrolled term |
Energy Time Series |
653 #4 - INDEX TERM--UNCONTROLLED |
Uncontrolled term |
LSTM |
700 0# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Amal Mohamed Abdelfattah , |
Relator term |
|
700 0# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Elhousainy Abdelbar Rady , |
Relator term |
|
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) |
Cataloger |
Amira |
Reviser |
Cataloger |
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) |
Cataloger |
Nazla |
Reviser |
Revisor |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Koha item type |
Thesis |