An empirical comparison of Clustering using hierarchical methods and K-means

Praveen, P.; Rama, B.

doi:10.1109/aeeicb.2016.7538328

Cited by 20 publications

(7 citation statements)

References 9 publications

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“…The results of cluster analysis reveal internal data structure and improve understanding of data. There are many cluster algorithms that are available for data partitioning into clusters and k-means being a popular algorithm apportions each data point in data set in such a fashion that it falls in just one cluster (Praveen & Rama, 2016). Fuzzy k-means cluster analysis was done and the optimum number of clusters were obtained by using FuzME software (Davatgar et al, 2012;Minasny & McBratney, 2002).…”

Section: Fuzzy Cluster Algorithm Analysismentioning

confidence: 99%

Soil mapping and delineation of management zones in the Western Ghats of coastal India

et al. 2018

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The pace of land degradation has almost doubled across the Western Ghats of India, one of the world's ‘hotspots’ for biodiversity, owing to soil erosion, mining, and rampant urbanization. The arising nutrient depletion leading to land degradation is thus a serious threat to agricultural sustainability in this region. Delineation of spatial soil property maps for nutrient management is an effective strategy for precision agriculture. The present investigation was carried out in North Goa District in Western Ghats, a seldom researched domain in the Indian coastal region. The study involved spatial array analysis of soil properties of 383 georeferenced soil samples and used fuzzy k‐means clustering for delineation of management zones (MZs). Soils were found highly acidic with low available N, P, and medium exchangeable K with a widespread Zn, Cu, and Fe deficiency and sporadic salinity. Soil properties exhibited low to high levels of skewness except for soil pH and Mn. Correlations between soil pH and K, Zn, and Mn, between EC and Fe, between soil organic carbon (SOC) and N, P, K, Cu, and Mn was positive and significant (P = 0.01). Geostatistical analysis revealed varied distribution pattern for soil properties with Gaussian (pH, P, and Cu), spherical (EC), stable (SOC), hole effect (N), K‐Bessel (K and Fe), exponential (Zn), and circular (Mn) as best fit semivariogram models with weak and strong spatial dependence. The spatial variability was mapped, and two MZs were delineated. The developed maps will be crucial in site‐specific nutrient management for agricultural and ecological sustainability in the Western Ghats of India.

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Section: Fuzzy Cluster Algorithm Analysismentioning

confidence: 99%

Soil mapping and delineation of management zones in the Western Ghats of coastal India

et al. 2018

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“…They are applicable to medium-sized datasets. The most representative is the k-means clustering [15]. -Hierarchical methods: they derive multiple cluster subdivisions, exploit the tree structure and use different threshold values within each cluster and inhomogeneity thresholds between distinct clusters [16].…”

Section: Clustering Methodsmentioning

confidence: 99%

A Wafer Bin Map “Relaxed” Clustering Algorithm for Improving Semiconductor Production Yield

Gallo

Capozzi

2020

Open Computer Science

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The semiconductor manufacturing process involves long and complex activities, with intensive use of resources. Producers compete through the introduction of new technologies for increasing yield and reducing costs. So, yield improvement is becoming increasingly important since advanced production technologies are complex and interrelated. In particular, Wafer Bin Maps (WBMs) presenting specific fault models provide crucial information to keep track of process problems in semiconductor manufacturing. Production control is often based on the “judgement” of expert engineers who, however, carry out the analysis of map templates through simple visual exploration. In this way, existing studies are subjective, time consuming, and are also limited by the capacity of human recognition. This study proposes a network-based data mining approach, which integrates correlation graphs with clustering analysis to quickly extract patterns from WBMs and then bind them to manufacturing defects. An empirical study has been conducted on real production data for validating the proposed clustering algorithm, which showed a perfect correspondence between the malfunction patterns found by the algorithm and those discovered by human experts, so confirming the validity of our approach in its ability of correctly identifying actual defective patterns to help improving production yield.

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“…These agents could also be thought of visiting these locations through an abstract sense.Thoughthe actual execution is fastened by implanting a physical machine over mobile agents who tend to offer an acceptable mechanism for gathering knowledge from web. A typical example is a net spider agent [15] that visits and processes a series of websites by following machine readable text links called as net crawlers.…”

Section: Logically Mobilementioning

confidence: 99%

Novel Classification Scheme for Multi Agents

Shaik¹,

Praveen²,

Prakash³

2019

AJCST

Self Cite

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Multi agent is that the broader space that is developing at a fast pace towards analysis and development of distinct vary of topics. These areas agitate numerous methodologies towards the agent style and comprehensive classification theme. During this paper we tend to establish major mode aspects of software package agents, then provides an summary of existing ontologies, and combines the most effective aspects of those themes to propose a brand new classification scheme. So as an instance the classifications, the JACK Intelligent Agents design is delineate within the context of the theme.

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An empirical comparison of Clustering using hierarchical methods and K-means

Cited by 20 publications

References 9 publications

Soil mapping and delineation of management zones in the Western Ghats of coastal India

Soil mapping and delineation of management zones in the Western Ghats of coastal India

A Wafer Bin Map “Relaxed” Clustering Algorithm for Improving Semiconductor Production Yield

Novel Classification Scheme for Multi Agents

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