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Fuzzy clustering
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In relational and object-oriented database systems, fuzzy or uncertain data will always be naturally present. However, these systems have many limitations for handling complex data types of fuzzy nature. Therefore, to represent and process fuzzy data, they need a flexible and efficient fuzzy query system. To solve this challenge, this paper proposes two different approaches to increase the flexibility of the fuzzy interrogation system.
17p
viamancio
04-06-2024
0
0
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A study of the state of the theory of fuzzy sets shows that until recently in Russia there were almost no studies in the chemical sector of the economy and finance using fuzzy analysis and forecasting, although by that time all necessary prerequisites for modeling financial systems had been created. The current situation in Russia is characterized by a high degree of science lagging behind the requests of state and commercial supply chain management.
6p
longtimenosee10
26-04-2024
2
1
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To express the visions forged in the workshops to a wide range of data mining researchers and practitioners and foster active participation in the study of foundations of data mining, we edited this volume by involving extended and updated versions of selected papers presented at those workshops as well as some other relevant contributions. The content of this book includes studies of foundations of data mining from theoretical, practical, algorithmical, and managerial perspectives. The following is a brief summary of the papers contained in this book.
561p
haojiubujain08
01-11-2023
5
2
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In this paper will introduce an algorithm, which can improve the results of data partitioning with reliability and multiple fuzzifier. This algorithm is named TSSFC. The introduced method includes three steps namely as “labeled data with FCM”, “Data transformation”, and “Semi supervised fuzzy clustering with multiple point fuzzifiers”.
10p
visharma
20-10-2023
8
4
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Ebook "Service oriented and cloud computing" includes content: Aservice delivery framework to support opportunistic collaborations, probabilistic topic models for web services clustering and discovery, managing imprecise criteria in cloud service ranking with a fuzzy multi criteria decision making method, modeling quality attributes of cloud standby systems - a long term cost and availability model,... and other contents.
253p
haojiubujain07
20-09-2023
5
3
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Data clustering is applied in various fields such as document classification, dental Xray image segmentation, medical image segmentation, etc. Especially, clustering algorithms are used in satellite image processing in many important application areas, including classification of vehicles participating in traffic, logistics, classification of satellite images to forecast droughts, floods, forest fire, etc.
15p
vimulcahy
18-09-2023
2
2
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This study proposed a novel clustering method that employs density peak-based fuzzy c-means (DP-FCM) and forensic-based investigation (FBI) algorithms. The proposed method (denoted as DP-FBI-FCM) aims to provide an effective clustering technique that can exploit the global optimal solution for custom segmentation problems.
6p
viwarmachine
01-07-2023
4
2
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In this study, we propose a hybrid method encompassing PFCM and improved Cuckoo search to form the proposed PFCM-ICS. The proposed method has been evaluated on 4 data sets issued from the UCI Machine Learning Repository and compared with recent clustering algorithms such as FCM, PFCM, PFCM based on particle swarm optimization (PSO), PFCM based on CS.
13p
visirius
19-01-2023
11
4
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Bài viết Sử dụng mạng nơron min - max mờ trong chẩn đoán bệnh ung thư trình bày ứng dụng mô hình FMN cải tiến học bán giám sát kết hợp với việc sử dụng các thông tin bổ trợ cho phép giải quyết đồng thời cả hai vấn đề giảm số lượng hyper box và khả dụng cho các tập dữ liệu mà 100% số lượng mẫu chưa được gán nhãn. Mô hình sử dụng được gọi là SCFMM-D (Semi-clustering and Fuzzy Min Max neural network in Diagnosis).
3p
vimclaren
20-10-2022
9
2
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The inexpensive production costs might allow for dense deployments in the physical space. For example, consider a scenario where thousands of devices, socalled sensor nodes, are dropped from an aircraft into a remote terrain.
214p
spiritedaway36
26-11-2021
14
3
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Objectives: The main objective of the dissertation is to research and develop fuzzy clustering techniques on remote sensing image data in order to improve accuracy and improve clustering quality of clustering algorithms.
162p
armyofthedead
23-06-2021
22
3
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In this paper, a new hybrid meta-heuristic algorithm for FCP called BHHS which combines the power of existing meta-heuristic frameworks such as Black Hole and Harmony Search is proposed. These two algorithms cooperate and support each other. The Black Hole part of the algorithm has the goal to find good candidate solution while the Harmony Search part has the goal to generate new candidate solutions for Black Hole when the event horizon of the Black Hole occurs. In addition, new best solutions of these two components are exchanged with each other to improve the quality of the search.
7p
chauchaungayxua11
23-03-2021
15
1
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In this research, a hybrid approach of fuzzy clustering and particle swarm optimization method based on semi-supervised method for remote sensing imagery analysis (SFCM-PSO) is proposed to overcome the above disadvantages.
16p
trinhthamhodang1218
04-03-2021
13
1
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In this study, Sentinel–1A satellite imagery is used to extract the coastline in Phan Thiet City. The boundary between land and water is determined by a two–step process: fuzzy clustering and interactive thresholding. Subsequently, the coastline in the study area was extracted into vector form. Finally, this shoreline is compared to manually digitized shoreline. There are 350 locations considered to determine the distance between two shorelines, of which 274 locations (77%) are 0 to 5 m (equivalent to ½ pixel) and 76 (23%) locations are over 5 m.
10p
cothumenhmong8
05-11-2020
26
1
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Despite advances in the gene-set enrichment analysis methods; inadequate definitions of gene-sets cause a major limitation in the discovery of novel biological processes from the transcriptomic datasets. Typically, gene-sets are obtained from publicly available pathway databases, which contain generalized definitions frequently derived by manual curation.
13p
viflorida2711
30-10-2020
9
3
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Uptake of colorectal cancer screening is low in the English NHS Bowel Cancer Screening Programme (BCSP). Participation in screening is strongly associated with socioeconomic status.
9p
vidhaka2711
31-07-2020
7
2
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The aim of this paper is to show how to choose the best clustering algorithms based on density-based clustering and present a new clustering algorithm for both crisp and fuzzy variables.
14p
kelseynguyen
26-05-2020
6
0
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This paper deals with the problem of grouping a set of objects into clusters. The objective is to minimize the sum of squared distances between objects and centroids. This problem is important because of its applications in different areas. In prior literature on this problem, attributes of objects have often been assumed to be crisp numbers.
12p
toritori
11-05-2020
23
0
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In this paper, a novel FTS forecasting model based on fuzzy C-means (FCM) clustering and particle swarm optimization (PSO) was developed to enhance the forecasting accuracy. Firstly, the FCM clustering is used to divide the historical data into intervals with different lengths. After generating interval, the historical data is fuzzified into fuzzy sets.
26p
viconandoyle2711
29-08-2019
34
2
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A novel two-stage fraud detection system in mobile telecom networks has been presented in this paper that identifies the malicious calls among the normal ones in two stages. Initially, a genetic algorithm-based optimized fuzzy c-means clustering is applied to the user’s historical call records for constructing the calling profile. Thereafter, the identification of the fraudulent calls occurs in two stages.
13p
vithanos2711
09-08-2019
28
1
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