scholarly journals Development of Multilayer-Based Map Matching to Enhance Performance in Large Truck Fleet Dispatching

2021 ◽  
Vol 10 (2) ◽  
pp. 79
Author(s):  
Ching-Yun Mu ◽  
Tien-Yin Chou ◽  
Thanh Van Hoang ◽  
Pin Kung ◽  
Yao-Min Fang ◽  
...  
Keyword(s):  
Data Structures ◽  
Spatial Data ◽  
Spatial Information ◽  
Data Retrieval ◽  
Spatial Data Mining ◽  
Map Matching ◽  
Matching Algorithm ◽  
Table Method ◽  
Look Up Table ◽  
The Look

Spatial information technology has been widely used for vehicles in general and for fleet management. Many studies have focused on improving vehicle positioning accuracy, although few studies have focused on efficiency improvements for managing large truck fleets in the context of the current complex network of roads. Therefore, this paper proposes a multilayer-based map matching algorithm with different spatial data structures to deal rapidly with large amounts of coordinate data. Using the dimension reduction technique, the geodesic coordinates can be transformed into plane coordinates. This study provides multiple layer grouping combinations to deal with complex road networks. We integrated these techniques and employed a puncture method to process the geometric computation with spatial data-mining approaches. We constructed a spatial division index and combined this with the puncture method, which improves the efficiency of the system and can enhance data retrieval efficiency for large truck fleet dispatching. This paper also used a multilayer-based map matching algorithm with raster data structures. Comparing the results revealed that the look-up table method offers the best outcome. The proposed multilayer-based map matching algorithm using the look-up table method is suited to obtaining competitive performance in identifying efficiency improvements for large truck fleet dispatching.

Unsupervised spatial data mining for the development of future scenarios: a Covid-19 application

2021 ◽  
pp. 173-178
Author(s):  
Yuri Calleo ◽  
Simone Di Zio
Keyword(s):  
Data Mining ◽  
Spatial Data ◽  
Latent Dirichlet Allocation ◽  
Spatial Information ◽  
Influence Factor ◽  
Influence Factors ◽  
Spatial Data Mining ◽  
Key Factors ◽  
Scenario Development ◽  
Data Mining Technique

In the context of Futures Studies, the scenario development process permits to make assumptions on what the futures can be in order to support better today decisions. In the initial stages of the scenario building (Framing and Scanning phases), the process requires much time and efforts to scanning data and information (reading of documents, literature review and consultation of experts) to understand more about the object of the foresight study. The daily use of social networks causes an exponential increase of data and for this reason here we deal with the problem of speeding up and optimizing the Scanning phase by applying a new combined method based on the analysis of tweets with the use of unsupervised classification models, text-mining and spatial data mining techniques. For the purpose of having a qualitative overview, we applied the bag-of-words model and a Sentiment Analysis with the Afinn and Vader algorithms. Then, in order to extrapolate the influence factors, and the relevant key factors (Kayser and Blind, 2017; 2020) the Latent Dirichlet Allocation (LDA) was used (Tong and Zhang, 2016). Furthermore, to acquire also spatial information we used spatial data mining technique to extract georeferenced data from which it was possible to analyse and obtain a geographic analysis of the data. To showcase our method, we provide an example using Covid-19 tweets (Uhl and Schiebel, 2017), upon which 5 topics and 6 key factors have been extracted. In the last instance, for each influence factor, a cartogram was created through the relative frequencies in order to have a spatial distribution of the users discussing each particular topic. The results fully answer the research objectives and the model used could be a new approach that can offer benefits in the scenario developments process.

scholarly journals Observing crosswind over urban terrain using scintillometer and Doppler lidar

2015 ◽  
Vol 8 (4) ◽  
pp. 1901-1911 ◽  
Author(s):  
D. van Dinther ◽  
C. R. Wood ◽  
O. K. Hartogensis ◽  
A. Nordbo ◽  
E. J. O'Connor
Keyword(s):  
Urban Environment ◽  
Wind Component ◽  
Doppler Lidar ◽  
Spectrum Method ◽  
Table Method ◽  
Look Up Table ◽  
Urban Terrain ◽  
Time Lagged ◽  
The Look ◽  
Lagged Correlation

Abstract. In this study, the crosswind (wind component perpendicular to a path, U⊥) is measured by a scintillometer and estimated with Doppler lidar above the urban environment of Helsinki, Finland, for 15 days. The scintillometer allows acquisition of a path-averaged value of U⊥ (U⊥), while the lidar allows acquisition of path-resolved U⊥ (U⊥ (x), where x is the position along the path). The goal of this study is to evaluate the performance of scintillometer U⊥ estimates for conditions under which U⊥ (x) is variable. Two methods are applied to estimate U⊥ from the scintillometer signal: the cumulative-spectrum method (relies on scintillation spectra) and the look-up-table method (relies on time-lagged correlation functions). The values of U⊥ of both methods compare well with the lidar estimates, with root-mean-square deviations of 0.71 and 0.73 m s−1. This indicates that, given the data treatment applied in this study, both measurement technologies are able to obtain estimates of U⊥ in the complex urban environment. The detailed investigation of four cases indicates that the cumulative-spectrum method is less susceptible to a variable U⊥ (x) than the look-up-table method. However, the look-up-table method can be adjusted to improve its capabilities for estimating U⊥ under conditions under for which U⊥ (x) is variable.

scholarly journals Performance of a New Enhanced Topological Decision-Rule Map-Matching Algorithm for Transportation Applications

2012 ◽  
Vol 10 (6) ◽  
Author(s):  
C. Blazquez ◽  
P. Miranda ◽  
A. Ponce
Keyword(s):  
Decision Rule ◽  
Spatial Data ◽  
Map Matching ◽  
Matching Algorithm ◽  
Matching Problems ◽  
Gps Technology ◽  
Special Cases ◽  
Data Points ◽  
Gis Environment ◽  
Transportation Applications

Map-matching problems arise in numerous transportation-related applications when spatial data is collected usinginaccurate GPS technology and integrated with a flawed digital roadway map in a GIS environment. This paperpresents a new enhanced post-processing topological decision-rule map-matching algorithm in order to addressrelevant special cases that occur in the spatial mismatch resolution. The proposed map-matching algorithm includessimple algorithmic improvements: dynamic buffer that varies its size to snap GPS data points to at least one roadwaycenterline; a comparison between vehicle heading measurements and associated roadway centerline direction; and anew design of the sequence of steps in the algorithm architecture. The original and new versions of the algorithmwere tested on different spatial data qualities collected in Canada and United States. Although both versionssatisfactorily resolve complex spatial ambiguities, the comparative and statistical analysis indicates that the newalgorithm with the simple algorithmic improvements outperformed the original version of the map-matching algorithm.

Using a look-up table technique and finite element calculations for quick detection of stiff inclusions in silicone rubber

2020 ◽  
Vol 37 (6) ◽  
pp. 2137-2153
Author(s):  
Ulf G. Jonsson ◽  
Olof A. Lindahl ◽  
Britt M. Andersson
Keyword(s):  
Finite Element ◽  
Silicone Rubber ◽  
Lamb Wave ◽  
Spatial Information ◽  
Expected Value ◽  
Fe Model ◽  
Matching Algorithm ◽  
Content Type ◽  
Look Up Table ◽  
Resonance Sensor

Purpose The aim of the study was to show that a new method, using a look-up table technique, can be used to detect the presence and position of an inclusion embedded in a tissue-like material. Due to the time-consuming nature of the finite element (FE) method or FEM, real-time applications involving FEM as part of a control loop, are traditionally limited to slowly varying systems. By using a simplified two-dimensional FE model and a look-up table, we show by simulations and experiments that it is possible to achieve reasonable computational times in a tactile resonance sensor application. Design/methodology/approach A piezoelectric disk was placed in the center of a silicone rubber disk (SRD) with viscoelastic properties, where it acted as both sensor and actuator and dissipated radial acoustic waves into the silicone. The look-up table was constructed by calculating the radial Lamb wave transition frequencies in the impedance frequency response of the sensor while varying the position of an inclusion. A position-matching algorithm was developed that matched measured and calculated Lamb wave transitions and thereby identified the presence and position of an inclusion. Findings In an experiment, the position of a hard inclusion was determined by measuring the Lamb transition frequencies of the first radial resonance in two SRDs. The result of the matching algorithm for Disk 1 was that the matched position was less than 3% from the expected value. For Disk 2, the matching algorithm erroneously reported two false positions before reporting a position that was less than 5% from the expected value. An explanation for this discrepancy is presented. In a verifying experiment, the algorithm identified the condition with no inclusion present. Originality/value The approach outlined in this work, adds to the prospect of developing time-sensitive diagnostic instruments. This approach has the potential to provide a powerful technique to quickly present spatial information on detected tumors.

scholarly journals Applications of FP-Growth and Apriori Algorithm for Mining Fuzzified Spatial Dataset

2019 ◽  
Vol 9 (2) ◽  
pp. 2405-2411
Keyword(s):  
Data Mining ◽  
Spatial Data ◽  
Spatial Information ◽  
Research Work ◽  
Spatial Relations ◽  
Spatial Data Mining ◽  
Current Approach ◽  
Standard Data ◽  
Computer Cartography ◽  
Spatial Vagueness

Spatial data, also called geospatial data, is term needed to describe data linked to or containing knowledgeable data about a particular location on Earth’s surface. Spatial data mining's primary goal is to uncover hidden complicated information from spatial & non-spatial information in spite of their enormous quantity and find the spatial relations density. Spatial Data Mining techniques, however, continue to be an expansion of individuals utilized in standard data mining. Spatial Data is an extremely challenging area since enormous quantities of spatial data have been obtained from the remote sensed to the GIS (Geographic Information Systems), ecological estimation, computer cartography, planning and many more. In a given paper, we only focus on an essential type of spatial vagueness termed as spatial fuzziness. Spatial fuzziness intakes the property of several spatial objects in certainty which don’t contain boundaries of sharp type and interiors or whose boundaries as well as interiors can't be determined in precise form. This paper provides the method for finding fuzzy spatial data of association rule. Association rules provided valuable data in the assessment of important correlations observed in big databases. Compared to the previous research work, the current approach for there search highlights the superiority over the same dataset in terms of time taken and generated rules. The rules generated tell about the occurrence of attributes. The results show that the current research is more efficient than that of the previous work and also less time-consuming.

DARCY RIBEIRO UNIVERSITY CAMPUS MAP – 2017- TECHNICAL NOTE

2018 ◽  
Vol 7 (2) ◽  
Author(s):  
Rafael Sanzio Araújo dos Anjos ◽  
Jose Leandro de Araujo Conceição ◽  
Jõao Emanuel ◽  
Matheus Nunes
Keyword(s):  
Spatial Data ◽  
Spatial Information ◽  
Technical Note ◽  
University Campus ◽  
Communication Tool ◽  
Sources Of Information ◽  
Data Manipulation ◽  
Geographic Space ◽  
The Many ◽  
New Generation

The spatial information regarding the use of territory is one of the many strategies used to answer and to inform about what happened, what is happening and what may happen in geographic space. Therefore, the mapping of land use as a communication tool for the spatial data made significant progress in improving sources of information, especially over the last few decades, with new generation remote sensing products for data manipulation.

Assessment of the look-up table using the tubular and bundle CHF data and modification of the bundle correction factor

Kerntechnik ◽  
2006 ◽  
Vol 71 (4) ◽  
pp. 192-202
Author(s):  
D. K. Chandraker ◽  
P. K. Vijayan ◽  
D. Saha ◽  
R. K. Sinha
Keyword(s):  
Correction Factor ◽  
Look Up Table ◽  
The Look
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