scholarly journals Applying Machine Learning to DEM Raster Images

Technologies ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 87
Author(s):  
Esra Alzaghoul ◽  
Mohammad Belal Al-Zoubi ◽  
Ruba Obiedat ◽  
Fawaz Alzaghoul
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Clustering Algorithm ◽  
High Elevation ◽  
Geospatial Data ◽  
Optimal Decision ◽  
Hidden Patterns ◽  
Interactive Map ◽  
Using Data ◽  
Elevation Model

Geospatial data analysis can be improved by using data-driven algorithms and techniques from the machine learning field. The aim of our research is to discover interrelationships among topographical data to support the decision-making process. In this paper, we extracted topographical geospatial data from digital elevation model (DEM) raster images, and we discovered hidden patterns among this data based on the K-means clustering algorithm, to uncover relationships and find clusters of elevation values for the area of Jordan. We introduce a method for querying and clustering geospatial data and we built an interactive map accordingly. The method discovers hidden patterns and uncovers relationships in given large datasets. We demonstrate the applicability of the method using the Jordan map and we report on geospatial data analysis and retrieval improvements. The results show that the optimal decision is in favor of four clusters (classes). The first class includes the high elevation values, the second class includes the very low elevation values, the third class includes the medium-high elevation values, and the fourth class includes the very high elevation values.

K-MEANS CLUSTERING ALGORITHM FOR SERVICE DATA ANALYSIS BASED ON CUSTOMERS COMBINATION

2018 ◽  
Vol 3 (1) ◽  
pp. 001
Author(s):  
Zulhendra Zulhendra ◽  
Gunadi Widi Nurcahyo ◽  
Julius Santony
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Clustering Algorithm ◽  
Customer Complaints ◽  
Using Data ◽  
Clustering Data ◽  
Service Data ◽  
Selection Of

In this study using Data Mining, namely K-Means Clustering. Data Mining can be used in searching for a large enough data analysis that aims to enable Indocomputer to know and classify service data based on customer complaints using Weka Software. In this study using the algorithm K-Means Clustering to predict or classify complaints about hardware damage on Payakumbuh Indocomputer. And can find out the data of Laptop brands most do service on Indocomputer Payakumbuh as one of the recommendations to consumers for the selection of Laptops.

Detection of a SARS-CoV-2 sequence with genosensors using data analysis based on information visualization and machine learning techniques

2021 ◽  
Author(s):  
Juliana Coatrini Soares ◽  
Andrey Coatrini Soares ◽  
Valquiria da Cruz Rodrigues ◽  
Pedro Ramon Almeida Oiticica ◽  
Paulo Augusto Raymundo-Pereira ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Information Visualization ◽  
Machine Learning Techniques ◽  
Gene Coding ◽  
Learning Techniques ◽  
Using Data ◽  
Viral Nucleocapsid

We report on genosensors to detect an ssDNA sequence from the SARS-CoV-2 genome, which mimics the GU280 gp10 gene (coding the viral nucleocapsid phosphoprotein), using four distinct principles of detection...

Interactive Map Using Data Visualization and Machine Learning

2020 ◽  
Author(s):  
Sandhya Harikumar ◽  
Viveka Mannam ◽  
Chiranjeeb Mahanta ◽  
Mounika Smitha ◽  
Shazia Zaman
Keyword(s):  
Machine Learning ◽  
Data Visualization ◽  
Interactive Map ◽  
Using Data

scholarly journals Artificial Intelligence

2019 ◽  
pp. 357-385
Author(s):  
Eric Guérin ◽  
Orhun Aydin ◽  
Ali Mahdavi-Amiri
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Virtual Reality ◽  
Data Analysis ◽  
Generative Models ◽  
Geospatial Data ◽  
Great Promise ◽  
Data Sets ◽  
Digital Earth ◽  
Data Analysis Methods

Abstract In this chapter, we provide an overview of different artificial intelligence (AI) and machine learning (ML) techniques and discuss how these techniques have been employed in managing geospatial data sets as they pertain to Digital Earth. We introduce statistical ML methods that are frequently used in spatial problems and their applications. We discuss generative models, one of the hottest topics in ML, to illustrate the possibility of generating new data sets that can be used to train data analysis methods or to create new possibilities for Digital Earth such as virtual reality or augmented reality. We finish the chapter with a discussion of deep learning methods that have high predictive power and have shown great promise in data analysis of geospatial data sets provided by Digital Earth.

scholarly journals Foreword to the Special Issue on Machine Learning for Geospatial Data Analysis

2018 ◽  
Vol 7 (4) ◽  
pp. 147 ◽  
Author(s):  
Jan Wegner ◽  
Ribana Roscher ◽  
Michele Volpi ◽  
Fabio Veronesi
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Geospatial Data ◽  
Special Issue

AKTUALISASI PEDIDIKAN KARAKTER DALAM PENGEMBANGAN REVOLUSI MENTAL BERBASIS ADIWIYATA DAN MULTIKULTURAL

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Suhardi Suhardi
Keyword(s):  
Data Analysis ◽  
Character Education ◽  
Achievement Motivation ◽  
Case Study Research ◽  
Individual Development ◽  
Human Beings ◽  
Soft Skill ◽  
Design Data ◽  
Strategic Role ◽  
Using Data

Mental revolution of education requires efforts to print educated human beings by having the motivation to meet the standards of achievement excellence, such as ethos of progress, ethics, achievement motivation, discipline, optimistic, productive, innovative and active views. This can be implemented with character education. Character education is one of the soft skill tools that can be integrated in learning in each subject. Learning activities using an active learning approach have a strategic role in instilling national character values so that students are able to behave and act on values that have become their personality. The purpose of this study was to find and analyze about: 1) Implementation of Character Education to Build Adiwiyata-Based Mental Revolution and Multiculturalism; 2) Implementation of Character Education to Build Mental Revolution in Organizational Culture. This study uses a qualitative approach with phenomenological naturatistics (phenomenology approach), with a descriptive type of case study research design. Data were analyzed using data analysis techniques: data reduction, data analysis and conclusions. The results of the study are: The application of character education to develop a mental revolution can be started from the character of building the environment. Environmental character is very important for individual development. The implementation of character education in building a mental revolution can emphasize the internalization of multicultural values and Adiwiyata which in the end will form a loving environmental awareness and foster a spirit of tolerance.

Peranan Ketua Pengurus dan Manajer Dalam Penyusunan dan Penerapan Laporan Keuangan Berbasis SAK ETAP Pada Koperasi di Kota Palembang

2019 ◽  
Vol 14 (2) ◽  
pp. 119
Author(s):  
Riza Syahputera ◽  
Martha Rianty
Keyword(s):  
Data Analysis ◽  
Sampling Technique ◽  
Financial Statements ◽  
Significant Positive Effect ◽  
Analysis Technique ◽  
Regression Test ◽  
Using Data ◽  
The City ◽  
Positive Effect

AbstractThis study aims to determine the effect of the role of the Chairperson and Cooperative Manager in the preparation and application of Financial Statements based on SAK ETAP in cooperatives in the city of Palembang. This research is a quantitative study using data obtained from questionnaires and measured using a Likert scale. The sampling technique used is purposive sampling. The sample used in this study was the Chairperson of the cooperative and the manager of the cooperative in the city of Palembang. The cooperatives studied were 203 cooperatives. The data analysis technique used is multiple linear regression test. The results showed that the role of cooperative leaders and managers had a significant positive effect on the preparation and application of SAK ETAP-based financial statements.Keywords : chairman, manager, SAK ETAP, cooperative

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