An innovative approach to design cogeneration systems based on big data analysis and use of clustering methods

Vialetto, Giulio; Noro, Marco

doi:10.1016/j.enconman.2020.112901

Cited by 26 publications

(6 citation statements)

References 34 publications

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“…The k-means clustering technique and its variants have mostly been used in the energy sector clustering. Vialetto and Noro ( 2020 ) used the k-means clustering, silhouette method to define the number of clusters while clustering energy demand data. They used clustering in the design of cogeneration systems to allow energy-cost savings.…”

Section: Applications Of Clusteringmentioning

confidence: 99%

Data clustering: application and trends

Oyewole

Thopil

2022

Artif Intell Rev

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Clustering has primarily been used as an analytical technique to group unlabeled data for extracting meaningful information. The fact that no clustering algorithm can solve all clustering problems has resulted in the development of several clustering algorithms with diverse applications. We review data clustering, intending to underscore recent applications in selected industrial sectors and other notable concepts. In this paper, we begin by highlighting clustering components and discussing classification terminologies. Furthermore, specific, and general applications of clustering are discussed. Notable concepts on clustering algorithms, emerging variants, measures of similarities/dissimilarities, issues surrounding clustering optimization, validation and data types are outlined. Suggestions are made to emphasize the continued interest in clustering techniques both by scholars and Industry practitioners. Key findings in this review show the size of data as a classification criterion and as data sizes for clustering become larger and varied, the determination of the optimal number of clusters will require new feature extracting methods, validation indices and clustering techniques. In addition, clustering techniques have found growing use in key industry sectors linked to the sustainable development goals such as manufacturing, transportation and logistics, energy, and healthcare, where the use of clustering is more integrated with other analytical techniques than a stand-alone clustering technique.

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Section: Applications Of Clusteringmentioning

confidence: 99%

Data clustering: application and trends

Oyewole

Thopil

2022

Artif Intell Rev

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“…Tujuan utama dari proses ini adalah untuk pengelompokan sejumlah data/ objek ke dalam sebuah klaster sehingga dalam setiap klaster akan berisi data yang semirip mungkin (Nurjanah, dkk, 2014). Pada analisis klaster memungkinkan untuk pengelompokkan pada data yang besar sehingga penggunaannya menjadi lebih praktis (Vialetto & Noro, 2020;Ramos dkk, 2015;Alguliyev et al, 2021;Kucherov & Kurenkov, 2017).…”

Section: Metodeunclassified

Pemetaan untuk Strategi Dakwah di Kota Semarang Menggunakan Pendekatan Data Mining (Mapping for Da'wah Strategy in Semarang City Using Data Mining Approach)

Karim

Adeni

Fitri

et al. 2021

Jurnal Dakwah Risalah

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This paper aims to explore the potential of da'wah in the city of Semarang with a data mining approach. The data mining approach is carried out by implementing the fuzzy c-means (FCM) algorithm in order to obtain the optimum number of clusters in the potential clustering of da'wah in the city of Semarang. The data used in this study from the Ministry of Religion of the Republic of Indonesia and the Central Statistics Agency (BPS) of Semarang City. The results of the FCM analysis show that the optimum number of clusters is two clusters, where the sub-district in the second cluster is an area with a high potential for da'wah. This study provides information that in effective da'wah activities, certainty and clarity is needed regarding the targets of da'wah through mapping of da'wah in the form of clustering potential da'wah. This can be a consideration of dakwah strategies for the successful implementation of da'wah studies so that an increase in the target behavior of da'wah can be achieved. The application of FCM to get the optimum cluster of potential da'wah in order to produce da'wah mapping is novelty in the field of Islamic studies, especially the science of da'wah.

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“…Giulio et al used the cluster analysis method for energy demand data to design the cogeneration system. This approach helps to improve the energy efficiency of the cogeneration plant [38].…”

Section: Array-based Clustering Techniquesmentioning

confidence: 99%

Cell Production System Design: A Literature Review

Ghahremani-Nahr

Bathaee

Mazloumzadeh

et al. 2021

IJIMES

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In a cell production system, a number of machines that differ in function are housed in the same cell. The task of these cells is to complete operations on similar parts that are in the same group. Determining the family of machine parts and cells is one of the major design problems of production cells. Cell production system design methods include clustering, graph theory, artificial intelligence, meta-heuristic, simulation, mathematical programming. This article discusses the operation of methods and research in the field of cell production system design. Methodology:To examine these methods, from 187 articles published in this field by authoritative scientific sources, based on the year of publication and the number of restrictions considered and close to reality, which are searched using the keywords of these restrictions and among them articles Various aspects of production and design problems, such as considering machine costs and cell size and process routing, have been selected simultaneously.Findings: Finally, the distribution diagram of the use of these methods and the limitations considered by their researchers, shows the use and efficiency of each of these methods. By examining them, more efficient and efficient design fields of this type of production system can be identified.Originality/Value: In this article, the literature on cell production system from 1972 to 2021 has been reviewed.

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An innovative approach to design cogeneration systems based on big data analysis and use of clustering methods

Cited by 26 publications

References 34 publications

Data clustering: application and trends

Data clustering: application and trends

Pemetaan untuk Strategi Dakwah di Kota Semarang Menggunakan Pendekatan Data Mining (Mapping for Da'wah Strategy in Semarang City Using Data Mining Approach)

Cell Production System Design: A Literature Review

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