• Title/Summary/Keyword: Clustering Design

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Design of Fuzzy System with Hierarchical Classifying Structures and its Application to Time Series Prediction (계층적 분류구조의 퍼지시스템 설계 및 시계열 예측 응용)

  • Bang, Young-Keun;Lee, Chul-Heui
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.5
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    • pp.595-602
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    • 2009
  • Fuzzy rules, which represent the behavior of their system, are sensitive to fuzzy clustering techniques. If the classification abilities of such clustering techniques are improved, their systems can work for the purpose more accurately because the capabilities of the fuzzy rules and parameters are enhanced by the clustering techniques. Thus, this paper proposes a new hierarchically structured clustering algorithm that can enhance the classification abilities. The proposed clustering technique consists of two clusters based on correlationship and statistical characteristics between data, which can perform classification more accurately. In addition, this paper uses difference data sets to reflect the patterns and regularities of the original data clearly, and constructs multiple fuzzy systems to consider various characteristics of the differences suitably. To verify effectiveness of the proposed techniques, this paper applies the constructed fuzzy systems to the field of time series prediction, and performs prediction for nonlinear time series examples.

User-Participated Design Method for Perforated Metal Facades using Virtual Reality (가상현실 기반 사용자 참여형 타공패널 파사드 설계 방법론)

  • Jang, Do-Jin;Kim, Seongjun;Kim, Sung-Ah
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.36 no.4
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    • pp.103-111
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    • 2020
  • Perforated metal sheets are used as panels of facades for controlling environmental factors while ensuring user's visibility. Despite their functional potentials, only a specific direction of facades or an orientation of a building was considered in the relevant studies. This study proposed a design methodology for the perforated panel facades that reflects the location on the facades and the user's requirements. The optimization of quantitative and qualitative performance is achieved through communication between designers and users in a VR system. In optimizing quantitative performances, designers use machine learning techniques such as clustering and genetic algorithm to allocate optimal panels on the facades. In optimizing qualitative performances, through the VR system, users intervene in evaluating performances whose preferences are depending on them. The experiment using the office project showed that designers were able to make decisions based on clustering using GMM to optimize multiple quantitative performances. The gap between the target and final performance could be narrowed by limiting the types of perforated panels considering mass customization. In assessing visibility as a qualitative performance, users were able to participate in the design process using the VR system.

Determining the Number and the Locations of RBF Centers Using Enhanced K-Medoids Clustering and Bi-Section Search Method (보정된 K-medoids 군집화 기법과 이분 탐색기법을 이용한 RBF 네트워크의 중심 개수와 위치와 통합 결정)

  • Lee, Daewon;Lee, Jaewook
    • Journal of Korean Institute of Industrial Engineers
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    • v.29 no.2
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    • pp.172-178
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    • 2003
  • In the recent researches, a variety of ways for determining the locations of RBF centers have been proposed assuming that the number of RBF centers is known. But they have also many numerical drawbacks. We propose a new method to overcome such drawbacks. The strength of our method is to determine the locations and the number of RBF centers at the same time without any assumption about the number of RBF centers. The proposed method consists of two phases. The first phase is to determine the number and the locations of RBF centers using bi-section search method and enhanced k-medoids clustering which overcomes drawbacks of clustering algorithm. In the second phase, network weights are computed and the design of RBF network is completed. This new method is applied to several benchmark data sets. Benchmark results show that the proposed method is competitive with the previously reported approaches for center selection.

On 5-Axis Freeform Surface Machining Optimization: Vector Field Clustering Approach

  • My Chu A;Bohez Erik L J;Makhanov Stanlislav S;Munlin M;Phien Huynh N;Tabucanon Mario T
    • International Journal of CAD/CAM
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    • v.5 no.1
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    • pp.1-10
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    • 2005
  • A new approach based on vector field clustering for tool path optimization of 5-axis CNC machining is presented in this paper. The strategy of the approach is to produce an efficient tool path with respect to the optimal cutting direction vector field. The optimal cutting direction maximizes the machining strip width. We use the normalized cut clustering technique to partition the vector field into clusters. The spiral and the zigzag patterns are then applied to generate tool path on the clusters. The iso-scallop method is used for calculating the tool path. Finally, our numerical examples and real cutting experiment show that the tool path generated by the proposed method is more efficient than the tool path generated by the traditional iso-parametric method.

Granular Bidirectional and Multidirectional Associative Memories: Towards a Collaborative Buildup of Granular Mappings

  • Pedrycz, Witold
    • Journal of Information Processing Systems
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    • v.13 no.3
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    • pp.435-447
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    • 2017
  • Associative and bidirectional associative memories are examples of associative structures studied intensively in the literature. The underlying idea is to realize associative mapping so that the recall processes (one-directional and bidirectional ones) are realized with minimal recall errors. Associative and fuzzy associative memories have been studied in numerous areas yielding efficient applications for image recall and enhancements and fuzzy controllers, which can be regarded as one-directional associative memories. In this study, we revisit and augment the concept of associative memories by offering some new design insights where the corresponding mappings are realized on the basis of a related collection of landmarks (prototypes) over which an associative mapping becomes spanned. In light of the bidirectional character of mappings, we have developed an augmentation of the existing fuzzy clustering (fuzzy c-means, FCM) in the form of a so-called collaborative fuzzy clustering. Here, an interaction in the formation of prototypes is optimized so that the bidirectional recall errors can be minimized. Furthermore, we generalized the mapping into its granular version in which numeric prototypes that are formed through the clustering process are made granular so that the quality of the recall can be quantified. We propose several scenarios in which the allocation of information granularity is aimed at the optimization of the characteristics of recalled results (information granules) that are quantified in terms of coverage and specificity. We also introduce various architectural augmentations of the associative structures.

Retail Outlet Clustering of the Imported Automobile Distributors in Korea

  • Park, Koo-Woong
    • Journal of Distribution Science
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    • v.16 no.5
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    • pp.45-59
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    • 2018
  • Purpose - This paper aims to analyze the distinct pattern of clustering of imported automobile distributors and provide evidence for the phenomenon using Korean data. Research design, data, and methodology - In this paper, we use data from Korea Automobile Importers & Distributors Association of 23 foreign automobile brands to evaluate the degree of concentration of showrooms using locational Gini index. We identify possible causes for the high level of clustering from two perspectives; 1) on the distributors' side and 2) on the customers' side. Results - We find a very strong locational concentration of imported automobile showrooms within close vicinity in the major cities and districts in Korea. Locational Gini coefficients are 0.1024 at the national level, 0.1836~0.3763 at city level, and 0.3941~0.4311 at district level on a [0,0.5] scale. Conclusions - Luxury foreign automobile customers tend to shop extensively around multiple brands prior to their ideal model selection. Accordingly, the imported automobile distributors cluster together close to their direct competitors in order to give a good comparison opportunity for the potential customers. This will maximize the probability of the visits of potential customers and lead to successful sales performance.

Heterogeneity-aware Energy-efficient Clustering (HEC) Technique for WSNs

  • Sharma, Sukhwinder;Bansal, Rakesh Kumar;Bansal, Savina
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.4
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    • pp.1866-1888
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    • 2017
  • Efficient energy consumption in WSN is one of the key design issues for improving network stability period. In this paper, we propose a new Heterogeneity-aware Energy-efficient Clustering (HEC) technique which considers two types of heterogeneity - network lifetime and of sensor nodes. Selection of cluster head nodes is done based on the three network lifetime phases: only advanced nodes are allowed to become cluster heads in the initial phase; in the second active phase all nodes are allowed to participate in cluster head selection process with equal probability, and in the last dying out phase, clustering is relaxed by allowing direct transmission. Simulation-based performance analysis of the proposed technique as compared to other relevant techniques shows that HEC achieves longer stable region, improved throughput, and better energy dissipation owing to judicious consumption of additional energy of advanced nodes. On an average, the improvement observed for stability period over LEACH, SEP, FAIR and HEC- with SEP protocols is around 65%, 30%, 15% and 17% respectively. Further, the scalability of proposed technique is tested by varying the field size and number of sensing nodes. The results obtained are found to be quite optimistic. The impact of energy heterogeneity has also been assessed and it is found to improve the stability period though only upto a certain extent.

The Selective Transmission of Sensor Data for a Water Quality Monitoring System (수질 모니터링 시스템을 위한 센서 데이터의 선택적 전송방법)

  • Kwon, Dae-Hyeon;Oh, Ryeom-Duk;Cho, Soo-Sun
    • Journal of Internet Computing and Services
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    • v.11 no.4
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    • pp.51-58
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    • 2010
  • In this paper, we introduce various attempts to transmit sensor data efficiently for design of a water quality monitoring system under the USN environment. The representative methods are the sensor management on a sensor node and the clustering on a sink node. The sensor management includes controls of sensing intervals, data accumulations, and data transmissions. And the clustering is one of efficient data compression methods using data mining technology. From the experimental results we confirmed that the proposed transmission method using the sensor management and the clustering outperformed common transmission method.

An Energy Efficient Clustering Algorithm in Mobile Adhoc Network Using Ticket Id Based Clustering Manager

  • Venkatasubramanian, S.;Suhasini, A.;Vennila, C.
    • International Journal of Computer Science & Network Security
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    • v.21 no.7
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    • pp.341-349
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    • 2021
  • Many emerging mobile ad-hoc network application communications are group-oriented. Multicast supports group-oriented applications efficiently, particularly in a mobile environment that has a limited bandwidth and limited power. Energy effectiveness along with safety are 2 key problem in MANET design. Within this paper, MANET is presented with a stable, energy-efficient clustering technique. In this proposed work advanced clustering in the networks with ticket ID cluster manager (TID-CMGR) has formed in MANET. The proposed routing scheme makes secure networking the shortest route possible. In this article, we propose a Cluster manager approach based on TICKET-ID to address energy consumption issues and reduce CH workload. TID-CMGR includes two mechanism including ticket ID controller, ticketing pool, route planning and other components. The CA (cluster agent) shall control and supervise the functions of nodes and inform to TID-CMGR. The CH conducts and transfers packets to the network nodes. As the CH energy level is depleted, CA elects the corresponding node with elevated energy values, and all new and old operations are simultaneously stored by CA at this time. A simulation trial for 20 to 100 nodes was performed to show the proposed scheme performance. The suggested approach is used to do experimental work using the NS- simulator. TIDCMGR is compared with TID BRM and PSO to calculate the utility of the work proposed. The assessment shows that the proposed TICKET-ID scheme achieves 90 percent more than other current systems.

Distributed beamforming with one-bit feedback and clustering for multi-node wireless energy transfer

  • Lee, Jonghyeok;Hwang, SeongJun;Hong, Yong-gi;Park, Jaehyun;Byun, Woo-Jin
    • ETRI Journal
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    • v.43 no.2
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    • pp.221-231
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    • 2021
  • To resolve energy depletion issues in massive Internet of Things sensor networks, we developed a set of distributed energy beamforming methods with one-bit feedback and clustering for multi-node wireless energy transfer, where multiple singleantenna distributed energy transmitters (Txs) transfer their energy to multiple nodes wirelessly. Unlike previous works focusing on distributed information beamforming using a single energy receiver (Rx) node, we developed a distributed energy beamforming method for multiple Rx nodes. Additionally, we propose two clustering methods in which each Tx node chooses a suitable Rx node. Furthermore, we propose a fast distributed beamforming method based on Tx sub-clustering. Through computer simulations, we demonstrate that the proposed distributed beamforming method makes it possible to transfer wireless energy to massive numbers of sensors effectively and rapidly with small implementation complexity. We also analyze the energy harvesting outage probability of the proposed beamforming method, which provides insights into the design of wireless energy transfer networks with distributed beamforming.