Heuristic Data Merging for Constructing Initial Agent Populations

2017 ◽  
pp. 174-193
Author(s):  
Bhagya N. Wickramasinghe ◽  
Dhirendra Singh ◽  
Lin Padgham
Keyword(s):  
Data Merging ◽  
Initial Agent

scholarly journals Correction: Hu, Q., et al. Rainfall Spatial Estimations: A Review from Spatial Interpolation to Multi-Source Data Merging. Water 2019, 11, 579

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1936
Author(s):  
Qingfang Hu ◽  
Zhe Li ◽  
Leizhi Wang ◽  
Yong Huang ◽  
Yintang Wang ◽  
...  
Keyword(s):  
Spatial Interpolation ◽  
Data Merging ◽  
Source Data

The authors wish to make the following corrections to this paper [...]

Seismic events discrimination by neuro-fuzzy-based data merging

1998 ◽  
Vol 25 (18) ◽  
pp. 3449-3452 ◽  
Author(s):  
S. Muller ◽  
J. -F. Legrand ◽  
J.-D. Muller ◽  
Y. Cansi ◽  
R. Crusem ◽  
...  
Keyword(s):  
Seismic Events ◽  
Data Merging ◽  
Neuro Fuzzy

scholarly journals A Framework for Visualizing Heterogeneous Construction Data Using Semantic Web Standards

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Mostafa Ali ◽  
Yasser Mohamed
Keyword(s):  
Ad Hoc ◽  
3D Visualization ◽  
Heterogeneous Data ◽  
Data Merging ◽  
Levels Of Detail ◽  
Heterogeneous Data Sources ◽  
Web Standards ◽  
Visualization Process ◽  
Merging Process ◽  
Different Sources

3D Visualization provides a mean for communicating different construction activities to diverse audiences. The scope, level of detail, and time resolution of the 3D visualization process are determined based on the targeted audiences. Developing the 3D visualization requires obtaining and merging heterogeneous data from different sources (such as BIM model and CPM schedule). The data merging process is usually carried out on ad hoc basis for a specific visualization case which limits the reusability of the process. This paper discusses a framework for automatic merging of heterogeneous data to create a visualization. The paper describes developing an ontology which captures concepts related to the visualization process. Then, heterogeneous data sources that are commonly used in construction are fed into the ontology which can be queried to produce different visualization scenarios. The potential of this approach has been demonstrated by providing multiple visualization scenarios that cover different audiences, levels of detail, and time resolutions.

scholarly journals Generating Multi-Document Summarization using Data Merging Technique

2016 ◽  
Vol 138 (6) ◽  
pp. 6-8 ◽  
Author(s):  
G.V. Garje ◽  
S.V. Khaladkar ◽  
A.N. Khengare ◽  
J.M. Pawar ◽  
M.S. Vidhate
Keyword(s):  
Document Summarization ◽  
Data Merging ◽  
Using Data

scholarly journals Quantifying Conventional Electroencephalogram Recordings and Examining its Output Computation with a Quantitative Electroencephalogram

2021 ◽  
Vol 7 (2) ◽  
pp. 108-120
Author(s):  
Gregory Xavier ◽  
Anselm Su Ting ◽  
Norsiah Fauzan
Keyword(s):  
Comparative Analysis ◽  
Statistical Analysis ◽  
Mathematical Analysis ◽  
Brain Wave ◽  
Data Merging ◽  
Quantitative Electroencephalogram

Quantitative electroencephalogram enables mathematical analysis of neurological recordings while conventional electroencephalogram lacks the mathematical output; hence, its usage is limited to neurological experts. This study was to determine if quantified conventional electroencephalogram recordings were compatible and comparable with quantitative electroencephalogram recordings. A group of post-call doctors was recruited and subjected to an EEG recording using a conventional electroencephalogram followed by a quantitative electroencephalogram device. The patterns and quantified recording results were compared. A comparative analysis of the two recording sets did not find differences in the recording patterns and statistical analysis. The findings promoted the use of a readily available conventional electroencephalogram in quantitative brain wave studies and have cleared potential compatibility bias towards data merging.

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