Some Algorithms for “Bond Energy” Data Analysis, Including Simulated Annealing

1990 ◽  
pp. 139-152 ◽  
Author(s):  
Sylvia Schleutermann ◽  
Phipps Arabie ◽  
Lawrence J. Hubert ◽  
François Bronsard
Keyword(s):  
Simulated Annealing ◽  
Data Analysis ◽  
Bond Energy ◽  
Energy Data

Bond Energy Data Summarized

1995 ◽  
Vol 72 (5) ◽  
pp. 423 ◽  
Author(s):  
Nicholas K. Kildahl
Keyword(s):  
Bond Energy ◽  
Energy Data

A Smart Cloud-Based Energy Data Mining Agent Using Big Data Analysis Technology

Smart Science ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 175-183 ◽  
Author(s):  
Hsueh-Yuan Lin ◽  
Sheng-Yuan Yang
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Energy Data

An Efficient Genetic Simulated Annealing Association Rules Method

2010 ◽  
Vol 34-35 ◽  
pp. 927-931
Author(s):  
Jun Jie Cen ◽  
Guo Hong Gao ◽  
Ying Jun Wang
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Data Analysis ◽  
Association Rules ◽  
Association Rule ◽  
Web Site ◽  
Web Mining ◽  
Incremental Mining ◽  
Mining Technology

Association rule is one of the important models of Web mining. By analyzing the topology of web site, this paper brings forward an efficient genetic simulated annealing association rules method．It applies genetic algorithm，incremental mining technology to trace users access behavior and optimizes association rules，and forecast capable association rules which improves its precision．Finally, this paper gives out the data analysis of experiment and summarizes the characteristics of genetic mining．

scholarly journals Visualizing Big Energy Data: Solutions for This Crucial Component of Data Analysis

2018 ◽  
Vol 16 (3) ◽  
pp. 18-25 ◽  
Author(s):  
Rob J. Hyndman ◽  
Xueqin Liu ◽  
Pierre Pinson
Keyword(s):  
Data Analysis ◽  
Energy Data ◽  
Crucial Component

Application of ArcGIS/MATLAB/ SQL Server/ VC++ Mixed Programming in Solar Energy Engineering

2010 ◽  
Vol 171-172 ◽  
pp. 323-328 ◽  
Author(s):  
Shi Jun He ◽  
Yu Zhang ◽  
Yuan Yu
Keyword(s):  
Data Analysis ◽  
Solar Energy ◽  
Experimental Results ◽  
Sql Server ◽  
Computer Implementation ◽  
Energy Data ◽  
Mixed Programming ◽  
Energy Engineering

Computer implementation of the models in solar energy engineering is very important. This paper summarized the models and realized them by ArcGIS/MATLAB/ SQL Server/ VC++ mixed programming. The experimental results show that it is feasible to apply mixed programming in solar energy engineering. The storage and management of solar energy data are of good performance. The implementation brings convenience for the solar energy reasonably utilization. Further, it puts forward a new direction for solar energy data analysis and calculation.

scholarly journals Building energy data analysis by clustering measured daily profiles

2017 ◽  
Vol 122 ◽  
pp. 583-588 ◽  
Author(s):  
Andrii Zakovorotnyi ◽  
Axel Seerig
Keyword(s):  
Data Analysis ◽  
Building Energy ◽  
Energy Data
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