Results 21 to 30 of about 21,099 (238)
The Fréchet/Manhattan Distance and the Trajectory Anonymisation Problem [PDF]
, 2016 Mobile communication has grown quickly in the last two decades. Connections can be wirelessly established from almost any habitable place in the earth, leading to a plethora of connection-based tracking mechanisms, such as GPS, GSM, RFID, etc. Trajectories representing the movement of people are consequently being gathered and analysed in a daily basis.
Christof Ferreira Torres +1 more
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Indonesian Journal of Statistics and Its Applications, 2021 There are several algorithms to solve many problems in grouping data. Grouping data is also known as clusterization, clustering takes advantage to solve some problems especially in business. In this note, we will modify the clustering algorithm based on distance principle which background of K-means algorithm (Euclidean distance).
Said Al Afghani +1 more
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Fingerprint Identification for Attendance Using Euclidean Distance and Manhattan Distance
sinkron, 2023 Attendance is an action to confirm that someone is present at the office, school, or event. The use of attendance in an agency or company is really important as it can improve the level of discipline and productivity. However, the traditional way of doing attendance is considered less effective, less secure, and more difficult to organize. Therefore, a
Putra, Adya Zizwan +4 more
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The role of the Manhattan distance in antiferromagnetic ordering [PDF]
Physica A: Statistical Mechanics and its Applications, 1997 The lowest state of one- and two-dimensional antiferromagnetic Heisenberg systems for a given number of "up" and "down" spins shows preference for certain regular patterns of the minority spin direction. For the one-dimensional system this pattern is an even distribution with equal distances for the minority spins, whereas in the two-dimensional ...
Tielen, G.J. +4 more
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A Comparative Study of K-means Clustering Algorithms Using Euclidean and Manhattan Distance for Climate Data. [PDF]
المجلة العراقية للعلوم الاحصائيةThe K-means clustering algorithms (Random, K-means++, Canopy, and Farthest First) are unsupervised machine learning techniques designed to group data points based on their similarities. The study examined the effects of clustering algorithms and distance
Bakhshan Hamad
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Comparison of distance measurement on k-nearest neighbour in textual data classification
Jurnal Teknologi dan Sistem Komputer, 2020 One algorithm to classify textual data in automatic organizing of documents application is KNN, by changing word representations into vectors. The distance calculation in the KNN algorithm becomes essential in measuring the closeness between data ...
Wahyono Wahyono +4 more
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The Manhattan product of digraphs
Electronic Journal of Graph Theory and Applications, 2013 We study the main properties of a new product of bipartite digraphs which we call Manhattan product. This product allows us to understand the subjacent product in the Manhattan street networks and can be used to built other networks with similar good ...
Francesc Comellas +2 more
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Modify Manhattan Distance for Image Similarity
Open Journal of Science and Technology, 2020 A New measure is proposed for assessing the similarity among gray-scale images. The well-known Structural Similarity Index Measure (SSIM) has been designed using a statistical approach that fails under significant noise (lowPSNR). The proposed measure, denoted by Manhattan distance and STD, uses a combination of two parts: the first part is the ...
null Tasaddi Maalak Hanoun +1 more
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A Distance-Based Technique for Non-Manhattan Layout Analysis [PDF]
2009 10th International Conference on Document Analysis and Recognition, 2009 Layout analysis is a fundamental step in automatic document processing. Many different techniques have been proposed to perform this task. Some follow a top-down approach: they start by identifying the high level components of the page structure and then recursively split them until basic blocks are found.
Stefano Ferilli +3 more
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A Manhattan distance based hybrid recommendation system
International Journal of Applied Mathematics Electronics and Computers, 2023 Many online service providers use a recommendation system to assist their customers' decision-making by generating recommendations. Accordingly, this paper proposes a new recommendation system for tourism customers to make online reservations for hotels with the features they need, saving customers time and increasing the impact of personalized hotel ...
Begüm Uyanık, Günce Keziban Orman
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