scholarly journals A practical approach to cluster validation in the energy sector

2021 ◽  
Vol 4 (S3) ◽  
Author(s):  
Alexander Bogensperger ◽  
Yann Fabel
Keyword(s):  
Clustering Algorithms ◽  
Composite Index ◽  
Practical Method ◽  
Energy Sector ◽  
Cluster Validation ◽  
Use Of Data ◽  
Current State ◽  
Composite Indices ◽  
Silhouette Index ◽  
Cluster Validation Indices

AbstractWith increasing digitization, new opportunities emerge concerning the availability and use of data in the energy sector. A comprehensive literature review shows an abundance in available unsupervised clustering algorithms as well as internal, relative and external cluster validation indices (cvi) to evaluate the results. Yet, the comparison of different clustering results on the same dataset, executed with different algorithms and a specific practical goal in mind still proves scientifically challenging. A large variety of cvi are described and consolidated in commonly used composite indices (e.g. Davies-Bouldin-Index, silhouette-Index, Dunn-Index). Previous works show the challenges surrounding these composite indices since they serve a generalized cluster quality evaluation. However, this does not suit individual clustering goals in many cases. The presented paper introduces the current state of science, existing cluster validation indices and proposes a practical method to combine them to an individual composite index, using Multi Criteria Decision Analysis (mcda). The methodology is applied on two energy economic use cases for clustering load profiles of bidirectional electric vehicles and municipalities.

scholarly journals Evaluating Sustainable Development by Composite Index: Evidence from French Departments

2021 ◽  
Vol 13 (2) ◽  
pp. 761
Author(s):  
Jean Bonnet ◽  
Eva Coll-Martínez ◽  
Patricia Renou-Maissant
Keyword(s):  
Sustainable Development ◽  
Regional Scale ◽  
Composite Index ◽  
Energy Transition ◽  
Evaluation Framework ◽  
Sustainable Mobility ◽  
The Sustainable Development ◽  
Sustainable Performance ◽  
Composite Indices ◽  
Hierarchical Ascending Classification

Since the adoption of the Sustainable Development Goals by the United Nations, sustainability has been a key priority for European governments. While previous studies have investigated the associations between indicators of sustainable development, few have directly considered a multidimensional approach to assess and compare the performance of regions in terms of sustainable development. As such, a comprehensive assessment of regional sustainable performance is thus still needed. In this paper, the concept of sustainability relies on the construction of six composite indices (environment and natural resources, energy transition, sustainable mobility, economic dynamism, social cohesion and solidarity, and governance and citizenship) with the aim to provide an evaluation framework for empirically comparing the performance of the 96 metropolitan French Departments. Each dimension is explored by spatial autocorrelation analysis and Hierarchical Ascending Classification (HAC) to classify French Departments providing five different regional profiles of sustainable development. The findings make it possible to identify the strengths and weaknesses of the departments in the implementation of sustainable development. This approach provides the bases for a systematic monitoring of sustainable development policies at the regional scale.

scholarly journals Analysis of genetic association using hierarchical clustering and cluster validation indices

Genomics ◽  
2017 ◽  
Vol 109 (5-6) ◽  
pp. 438-445 ◽  
Author(s):  
Inti A. Pagnuco ◽  
Juan I. Pastore ◽  
Guillermo Abras ◽  
Marcel Brun ◽  
Virginia L. Ballarin
Keyword(s):  
Genetic Association ◽  
Hierarchical Clustering ◽  
Cluster Validation ◽  
Cluster Validation Indices

scholarly journals Mexico’s energy reform: experience and lessons of the energy sector transformation in South America

2018 ◽  
Vol 26 (4) ◽  
pp. 609-619
Author(s):  
Elvis Ojeda Kalluni ◽  
Elmira A Chadaeva
Keyword(s):  
South America ◽  
Energy Security ◽  
Energy Demand ◽  
Energy Sector ◽  
Important Place ◽  
Safe Delivery ◽  
Energy Complex ◽  
Current State ◽  
History Of ◽  
Energy Reform

The study of fuel and energy complex of Mexico occupies a very important place in the world’s leading research centers. Among Russian and foreign studies there are a number of works that consider the problems and peculiarities of fuel and energy complex of the countries of Latin America including Mexico. This article is devoted to the analysis of Mexico’s energy reform and use their experiences to transform the energy sector of the countries of South America. Presents the history of the Mexican energy reform. Discusses basic principles of energy reform and energy security of the country. It also examines the factors that Mexico should include in its energy policy and management system to ensure the safe delivery of energy across the country. Offers a brief overview of the current state of TEK of Mexico. Mexico has a large and varied potential for producing energy from renewable sources. With the recent opening of the energy sector, the country has the necessary conditions to attract major investments to develop projects on renewable energy. The liberalization of the sector allows Mexico to meet the growing energy demand and to diversify its productive matrix, creating at the same time as energy security and reduce greenhouse gases, positively affecting the environment. Reform of the energy sector of Mexico and the analysis of the sector in this country can be of great importance for the transformation of the energy sector in many countries of the region, especially in places such as Argentina, Brazil and Venezuela.

scholarly journals Experiments on Clustering Algorithms for Mixed and Incomplete Data

2019 ◽  
Vol 9 (2) ◽  
pp. 4778-4784
Keyword(s):  
Machine Learning ◽  
Experimental Study ◽  
Incomplete Data ◽  
Clustering Algorithms ◽  
Cluster Validation ◽  
Clustering Data

Clustering mixed and incomplete data is a goal of frequent approaches in the last years because its common apparition in soft sciences problems. However, there is a lack of studies evaluating the performance of clustering algorithms for such kind of data. In this paper we present an experimental study about performance of seven clustering algorithms which used one of these techniques: partition, hierarchal or metaheuristic. All the methods ran over 15 databases from UCI Machine Learning Repository, having mixed and incomplete data descriptions. In external cluster validation using the indices Entropy and V-Measure, the algorithms that use the last technique showed the best results. Thus, we recommend metaheuristic based clustering algorithms for clustering data having mixed and incomplete descriptions.

SeqPAM

2008 ◽  
pp. 17-38 ◽  
Author(s):  
Pradeep Kumar Kumar ◽  
Raju S. Bapi ◽  
P. Radha Krishna
Keyword(s):  
Similarity Measure ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Similarity Measures ◽  
Sequential Data ◽  
Cluster Validation ◽  
Web Personalization ◽  
Similarity Preserving ◽  
Validation Technique ◽  
The Web

With the growth in the number of web users and necessity for making information available on the web, the problem of web personalization has become very critical and popular. Developers are trying to customize a web site to the needs of specific users with the help of knowledge acquired from user navigational behavior. Since user page visits are intrinsically sequential in nature, efficient clustering algorithms for sequential data are needed. In this paper, we introduce a similarity preserving function called sequence and set similarity measure S3M that captures both the order of occurrence of page visits as well as the content of pages. We conducted pilot experiments comparing the results of PAM, a standard clustering algorithm, with two similarity measures: Cosine and S3M. The goodness of the clusters resulting from both the measures was computed using a cluster validation technique based on average levensthein distance. Results on pilot dataset established the effectiveness of S3M for sequential data. Based on these results, we proposed a new clustering algorithm, SeqPAM for clustering sequential data. We tested the new algorithm on two datasets namely, cti and msnbc datasets. We provided recommendations for web personalization based on the clusters obtained from SeqPAM for msnbc dataset.

scholarly journals Impact of key factors on expected development of onshore wind energy sector in Poland and development scenarios

2018 ◽  
Vol 70 ◽  
pp. 01017 ◽  
Author(s):  
Izabela Wielewska ◽  
Karol Tucki ◽  
Anna Bączyk ◽  
Magda Trzaska
Keyword(s):  
Wind Energy ◽  
Wind Power ◽  
National Level ◽  
Wind Farms ◽  
Power Market ◽  
Energy Sector ◽  
Key Factors ◽  
Onshore Wind ◽  
Development Scenarios ◽  
Current State

The aim of the paper was to analyse the wind power market in Poland by reviewing the factors that shape and influence its current state and the possible development prospects. The paper was focused on legislative, environmental, manufacturing, sociocultural and economic factors. Barriers to the development of onshore wind power market and the expected development of wind energy in Poland in the years 2017-2020 were identified and measured based on a survey. The review of individual factors and the study performed present that legislative barriers and the introduction of the ‘distance act’ are factors with the biggest influence on the current stagnation of onshore wind energy sector. A review of the recommendations concerning the distance (from protected areas and housing) required to build wind farms set forth in literature shows that Poland is the only country with such harsh restrictions. With its good environmental conditions and technical capacities, Poland can become a European leader in the production of energy from wind. The only barrier is the legislative environment and political instability on the national level. Without improvements in this sector, there is no chance for new wind projects, as these factors are crucial for development of this type of energy.

scholarly journals Silhouette index for determining optimal k-means clustering on images in different color models

2018 ◽  
Vol 7 (2.14) ◽  
pp. 105 ◽  
Author(s):  
Abd Rasid Mamat ◽  
Fatma Susilawati Mohamed ◽  
Mohamad Afendee Mohamed ◽  
Norkhairani Mohd Rawi ◽  
Mohd Isa Awang
Keyword(s):  
Image Processing ◽  
Color Model ◽  
Cluster Validation ◽  
Validation Process ◽  
Color Models ◽  
Silhouette Index ◽  
Hsv Color Model ◽  
Different Color ◽  
Lab Color Model ◽  
Cie Lab

Clustering process is an essential part of the image processing. Its aim to group the data according to having the same attributes or similarities of the images. Consequently, determining the number of the optimum clusters or the best (well-clustered) for the image in different color models is very crucial. This is because the cluster validation is fundamental in the process of clustering and it reflects the split between clusters. In this study, the k-means algorithm was used on three colors model: CIE Lab, RGB and HSV and the clustering process made up to k clusters. Next, the Silhouette Index (SI) is used to the cluster validation process, and this value is range between 0 to 1 and the greater value of SI illustrates the best of cluster separation. The results from several experiments show that the best cluster separation occurs when k=2 and the value of average SI is inversely proportional to the number of k cluster for all color model. The result shows in HSV color model the average SI decreased 14.11% from k = 2 to k = 8, 11.1% in HSV color model and 16.7% in CIE Lab color model. Comparisons are also made for the three color models and generally the best cluster separation is found within HSV, followed by the RGB and CIE Lab color models.  

scholarly journals Spremembe v avifavni Kozjanskega parka med letoma 1999 in 2010: velik upad števila travniških ptic/ Changes in the avifauna of Kozjansko Park between 1999 and 2010: a large decline in the number of grassland birds

Acrocephalus ◽  
2014 ◽  
Vol 35 (162-163) ◽  
pp. 125-138
Author(s):  
Primož Kmecl ◽  
Tomaž Jančar ◽  
Tomaž Mihelič
Keyword(s):  
Grassland Birds ◽  
National Level ◽  
Composite Index ◽  
Natura 2000 ◽  
Generalist Species ◽  
Grassland Species ◽  
Composite Indices ◽  
Line Transects ◽  
Natura 2000 Site ◽  
Large Decline

Abstract In the 11 years between 1999 and 2010, certain groups of birds inhabiting Kozjansko Regional Park underwent a moderate or large decline. Composite indices for indicator species of different habitat types showed an increase of generalist species (composite index 108.3), a moderate decline of forest species (composite index 76.6) and species of extensively managed orchards (composite index 76.4), and a large decline of farmland (composite index 62.8) and grassland species (composite index 8.7). Our study was based on a census using line transects with an inner and outer belt. Randomly distributed line transects with a total length of 60.8 km were surveyed using the same method both in 1999 and 2010. The decline of farmland species mirrors the population trend of this group at the national level. The study area is protected by multiple nature conservation mechanisms. It is protected as a regional park and partly as a Natura 2000 site. These mechanisms, however, do not seem to be functioning here. We believe the large decline of grassland species is a consequence of agricultural policy, which favours a decrease of extensively managed grasslands.

scholarly journals COMPOSITE INDEX TO MEASURE THE PERFORMANCE OF TODAY’S CREATIVE CITIES: A HOLISTIC PERSPECTIVE

2019 ◽  
Vol 11 (2) ◽  
Author(s):  
Margarida RODRIGUES ◽  
Mário FRANCO
Keyword(s):  
Factor Analysis ◽  
Composite Index ◽  
Urban Sustainability ◽  
Theory And Practice ◽  
Decision Makers ◽  
Future Research ◽  
Political Decision ◽  
Creative Cities ◽  
Composite Indices ◽  
Overall Performance

The urgency to make today’s cities competitive has made political decision-makers focus on strategies oriented towards creativity, intelligence and urban sustainability. This scenario has led to the need to measure, assess and monitor the effects of those strategies on cities’ performance. Therefore, this study aims to present the scientific and robust weighting of the creativity, intelligence and urban sustainability dimensions in cities’ holistic, integrated and overall performance. Implicit in this objective is the previous construction of Composite Indices for each of those dimensions. In this context, the Exploratory Factor Analysis was found to be appropriate to respond to this aim, with empirical evidence being obtained in Portugal. The results show a weighting of 38%, 23.4% and 39.6% for creativity, intelligence and urban sustainability respectively. The contributions and implications for theory and practice, followed by indications for future research and the conclusions are also presented.

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