K-Means Clustering Optimization Using the Elbow Method and Early Centroid Determination Based on Mean and Median Formula

Umargono, Edy; Suseno, Jatmiko Endro; Gunawan, S K Vincensius

doi:10.2991/assehr.k.201010.019

Cited by 40 publications

(21 citation statements)

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“…For this reason, the next stage of analysis was to identify homogeneous areas in terms of calculated values of indexes for economic efficiency in macroeconomic accounting. For this purpose, the provinces were grouped using the K-Means method and assuming K = 3 [112]. As a result, for each farm type, these provinces were indicated, in which energy production using photovoltaic panels to cover the needs of farms showed low (group 1), medium (group 2), and high economic efficiency (group 3) (Figure 3).…”

Section: Resultsmentioning

confidence: 99%

Macroeconomic Efficiency of Photovoltaic Energy Production in Polish Farms

2021

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The public’s awareness of threats to the natural environment, as well as the hazard to human lives and health posed by the use of fossil fuels to generate energy has resulted in the growing interest in renewable energy sources, thus promoting attempts to reduce the dependency on conventional energy sources. Among the former, solar energy is one of the most promising. The aim of this study is to assess the macroeconomic efficiency of investments in photovoltaic installations to meet the demand for electricity of farms and agricultural production. Calculations were prepared for 48 variants comprising three farm types (dairy farms, field cropping farms, and mixed production farms), as well as 16 locations throughout Poland. The obtained results indicate high efficiency of electricity production using photovoltaic installations to cover the needs of farms in Poland. In macroeconomic accounting, NPV ranges from EUR 8200 to almost EUR 23,000, with the payback period depending on the farm type ranging from 4.3 up to 6 years, while the internal rate of return amounts to 21–32%. Increasing the scope of investments in photovoltaics (PV) to cover the electricity demand not only of the household, but also of the agricultural production leads to improved economic efficiency of energy production both in the macro- and microeconomic terms.

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Section: Resultsmentioning

confidence: 99%

Macroeconomic Efficiency of Photovoltaic Energy Production in Polish Farms

2021

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“…The primary purpose of the k-means clustering is to form clusters that "minimize the squared error criterion" using the predetermined number of k values, which represents the number of clusters (Ye et al, 2013). To obtain an optimal number of clusters, the Elbow Method's interpretation would be appropriate before applying k-means clustering (Bholowalia and Kumar, 2014;Syakur et al, 2018;Anuşlu and Fırat, 2019;Nainggolan et al, 2019;Cui, 2020;Liu and Deng, 2020;Umargono et al, 2020).…”

Section: Data Mining and Customer Segmentationmentioning

confidence: 99%

Discrete Event Simulation Model Performed with Data Analytics for a Call Center Optimization

Serper¹,

Şen²,

Uslu³

2022

ibr

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Optimization models enable organizations to find the best solution and respond to the demand from an uncertain environment and stochastic process promptly and with less engineering effort. This study aims to optimize the number of seasonal agents and customer prioritization needed for a call center system using big data analytics and discrete event simulations to improve customer satisfaction. The study was carried out based on data from a leading heating and ventilation company's call center. The K-means clustering technique was used to determine customer segmentation on 6-million-customer data. For prioritization, the making of a Recency-Frequency-Monetary (RFM) analysis was applied. The system was modeled using ARENA simulation software, and performance parameters were measured depending on the segments obtained. The results show that the simulation model performed with data analytics gives better results for a beneficial financial impact with numerical values in customer prioritization, reducing the average waiting time of the most prioritized customers by more than 90%, and for the least prioritized customers, it increased the average waiting time by approximately just 40%. However, with the company segments, the increase in the average waiting time of the least prioritized customers was approximately 300%.

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“…The elbow signs the point where the line represents its maximum curvature. Before we reach this point, an increase in the number of clusters helps to reduce the sum of squared errors [35]- [38].…”

Section: Cluster Validity Indicesmentioning

confidence: 99%

Geological domaining at Sungun porphyry copper deposit using cluster analysis

Nikfarjam

Hezarkhani

Aziz-Afshari

2022

GJCS

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Geometallurgical sampling has an important role in the geometallurgical programme. There are some critical aspects to be considered in geometallurgical sampling. Cluster analysis (CA) is one of the most popular methods that aids in creating domains. This study aims to use CA to create Geological domaining at the Sungun porphyry copper deposit (SPCD). Geological domains of SPCD were defined using PCA and K-means clustering with one hot encoding algorithm. Categorical data were encoded with one hot method and then PCA was used to condense the large new data set to its relevant features. In this research, we have exploited two validity indices to define the optimum number of clusters, namely the silhouette index and the elbow method. Therefore, clustering was performed using four clusters and geological domains were partitioned. The richest domain in this deposit is the second cluster in which the average grades of Cu and Mo are higher than in other clusters. Keywords: Cluster analysis, geological domains, K-means, PCA, Sungun deposit;

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K-Means Clustering Optimization Using the Elbow Method and Early Centroid Determination Based on Mean and Median Formula

Cited by 40 publications

References 0 publications

Macroeconomic Efficiency of Photovoltaic Energy Production in Polish Farms

Macroeconomic Efficiency of Photovoltaic Energy Production in Polish Farms

Discrete Event Simulation Model Performed with Data Analytics for a Call Center Optimization

Geological domaining at Sungun porphyry copper deposit using cluster analysis

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