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Dislocation detection in field environments: A belief functions contribution
- Source :
- Expert Systems with Applications, Expert Systems with Applications, Elsevier, 2012, 39 (10), pp.8505-8513. ⟨10.1016/j.eswa.2011.12.014⟩, Expert Systems with Applications, 2012, 39 (10), pp.8505-8513. ⟨10.1016/j.eswa.2011.12.014⟩
- Publication Year :
- 2012
- Publisher :
- HAL CCSD, 2012.
-
Abstract
- Highlights? The greedy acceptance criterion for the glowworms updating positions is proposed. ? The new formulas for the glowworms movement are proposed. ? Uniform design experiments were investigated the effect of parameters. ? The proposed improvement algorithms were effective than the classical algorithm. Dislocation is defined as the change between discrete sequential locations of critical items in field environments such as large construction projects. Dislocations on large sites of materials and critical items for which discrete time position estimates are available represent critical state changes. The ability to detect dislocations automatically for tens of thousands of items can ultimately improve project performance significantly. Detecting these dislocations in a noisy information environment where low cost radio frequency identification tags are attached to each piece of material, and the material is moved sometimes only a few meters, is the main focus of this study. We propose in this paper a method developed in the frame of belief functions to detect dislocations. The belief function framework is well-suited for such a problem where both uncertainty and imprecision are inherent to the problem. We also show how to deal with the calculations. This method has been implemented in a controlled experimental setting. The results of these experiments show the ability of the proposed method to detect materials dislocation over the site reliably. Broader application of this approach to both animate and inanimate objects is possible.
- Subjects :
- GPS
0211 other engineering and technologies
Construction materials
02 engineering and technology
Machine learning
computer.software_genre
Field (computer science)
Dislocation detection
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Artificial Intelligence
Position (vector)
021105 building & construction
0202 electrical engineering, electronic engineering, information engineering
Radio-frequency identification
Mathematics
RFID
business.industry
Frame (networking)
General Engineering
Function (mathematics)
belief functions
Sensors network
Computer Science Applications
Discrete time and continuous time
Global Positioning System
020201 artificial intelligence & image processing
Artificial intelligence
business
Focus (optics)
Algorithm
computer
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Subjects
Details
- Language :
- English
- ISSN :
- 09574174
- Database :
- OpenAIRE
- Journal :
- Expert Systems with Applications, Expert Systems with Applications, Elsevier, 2012, 39 (10), pp.8505-8513. ⟨10.1016/j.eswa.2011.12.014⟩, Expert Systems with Applications, 2012, 39 (10), pp.8505-8513. ⟨10.1016/j.eswa.2011.12.014⟩
- Accession number :
- edsair.doi.dedup.....59dcba8edfb2c2385b231d58e15c4701