• 제목/요약/키워드: Correlation clustering

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플라스틱 표면 조도의 변화에 따른 빈도분포에 대한 감성공학적 군집분석 (Clustering Kansei Factors for the Roughness of Plastic Surface Based on Frequency Distribution)

  • 전창림
    • 공업화학
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    • 제18권4호
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    • pp.366-370
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    • 2007
  • 신제품을 개발할 때 인간의 감성 즉 시각, 청각, 후각, 미각, 촉각에 대한 소비자의 반응에 대한 정보는 대단히 중요하다. 이제까지 촉각에 대한 연구는 다른 감성에 비하여 상대적으로 취약하였던 바, 본 연구에서는 각기 다른 표면 조도를 갖는 플라스틱 시료들에 대하여 체계적인 연구를 시도하였다. 37쌍의 긍정적과 부정적 형용사로 감성적 반응을 조사하여 통계적으로 분석하고 표면 조도와 인간 감성과의 관계를 분석하였다. 일반적으로 사용되는 평균선호도가 아닌 최선빈도를 사용하여 요인분석, 다변량척도분석, 군집분석들을 수행하였다.

GA 기반 TSK 퍼지 분류기의 설계와 응용 (A Design of GA-based TSK Fuzzy Classifier and Its Application)

  • 곽근창;김승석;유정웅;김승석
    • 한국지능시스템학회논문지
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    • 제11권8호
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    • pp.754-759
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    • 2001
  • 본 논문은 주성분분석기법, 퍼지 클러스터링, ANFIS(Adaptive Neuro-Fuzzy Inference System)와 하이브리드 GA(Hybrid Genetic Algorithm)를 이용하여 GA 기반 TSK(Takagi-Sugeno-Kang) 퍼지 분류기를 제안한다. 먼저 구조동정은 주성분분석기법을 이용하여 데이터 성분간의 상관관계가 제거하도록 입력데이터를 변환하고, FCM(Fuzzy c-means) 클러스터링과 ANFIS의 융합을 통해 초기 TSK 퍼지 분류기를 구축한다. 구축된 초기 분류기의 파라미터를 초기집단으로 발생시켜 AGA(Adaptive GA)와 RLSE(Recursive Least Square Estimate)에 의해 파라미터 동정을 수행한다. 이렇게 함으로서 퍼지 클러스터링의 효율적인 입력공간분할로 ANFIS의 문제점을 해결할 수 있고, AGA에 의해 집단의 다양성 유지와 전역적인 최적해의 수렴을 가속화할 수 있다. 마지막으로, 제안된 방법은 Iris 데이터 분류문제에 적용하여 이전의 다른 논문에 비해 좋은 성능을 보임을 알 수 있었다.

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Taxonomic implications of multivariate analyses of Egyptian Ononis L. (Fabaceae) based on morphological traits

  • FAYED, Abdel Aziz A.;EL-HADIDY, Azza M.H.;FARIED, Ahmed M.;OLWEY, Asmaa O.
    • 식물분류학회지
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    • 제49권1호
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    • pp.13-27
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    • 2019
  • Numerical taxonomy is employed to determine the phenetic proximity of the Egyptian taxa belonging to the genus Ononis L. A classical clustering analysis and a principal component analysis (PCA) were used to separate 57 macro- and micromorphological characters in order to circumscribe 11 taxa of Ononis. A clustering analysis using the unweighted pair-group method with the arithmetic means (UPGMA) method gives the highest co-phenetic correlation. Results from clustering and PCA revealed the segregation of five groups. Our results are in line, to some certain degree, with the traditional sub-sectional concept, as can be seen in the grouping of the representative members of the subsections Diffusae and Mittisimae together and the representative members of the subsections Viscosae and Natrix. The phenetic uniqueness of Ononis variegata and O. reclinata subsp. mollis was formally established. However, our findings contradict the classic sectional concept; this opinion was suggested earlier in previous phylogenetic circumscriptions of the genus. The most useful characters that provide taxonomic clarity were discussed.

Mapping the real-space distributions of galaxies in SDSS DR7

  • Shi, Feng
    • 천문학회보
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    • 제44권1호
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    • pp.78.1-78.1
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    • 2019
  • Using a method to correct redshift space distortion (RSD) for individual galaxies, we mapped the real space distributions of galaxies in the Sloan Digital Sky Survey (SDSS) Data Release 7(DR7). We use an ensemble of mock catalogs to demonstrate the reliability of this extension, showing that it allows for an accurate recovery of the real-space correlation functions and galaxy biases. We also demonstrate that, using an iterative method applied to intermediate scale clustering data, we can obtain an unbiased estimate of the growth rate of structure $f\sigma_8$, which is related to the clustering amplitude of matter, to an accuracy of $\sim 10\%$. Applying this method to the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7), we construct a real-space galaxy catalog spanning the redshift range $0.01 \leq z \leq 0.2$, which contains 584,473 galaxies in the North Galactic Cap (NGC). Using this data we, infer $0.376 \pm 0.038$ at a median redshift z=0.1, which is consistent with the WMAP9 cosmology at $1\sigma$ level. By combining this measurement with the real-space clustering of galaxies and with galaxy-galaxy weak lensing measurements for the same sets of galaxies, we are able to break the degeneracy between $f$, $\sigma_8$ and $b$. From the SDSS DR7 data alone, we obtain the following cosmological constraints at redshift $z=0.1$ for galaxies.

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Constraints on cosmology and baryonic feedback by the combined analysis of weak lensing and galaxy clustering with the Deep Lens Survey

  • Yoon, Mijin;Jee, M. James;Tyson, Tony
    • 천문학회보
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    • 제43권2호
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    • pp.41.1-41.1
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    • 2018
  • We constrain cosmological parameters by combining three different power spectra measured from galaxy clustering, galaxy-galaxy lensing, and cosmic shear using the Deep Lens Survey (DLS). Two lens bins (centered at z~0.27 and 0.54) and two source bins (centered at z~0.64, and 1.1) containing more than one million galaxies are selected to measure the power spectra. We re-calibrate the initial photo-z estimation of the lens bins by matching with SHELS and PRIMUS and confirm its fidelity by measuring a cross-correlation between the bins. We also check the reliability of the lensing signals through the null tests, lens-source flipping and cross shear measurement. Residual systematic errors from photometric redshift and shear calibration uncertainties are marginalized over in the nested sampling during our parameter constraint process. For the flat LCDM model, we determine S_8=sigma_8(Omega_m/0.3)^0.5=0.832+-0.028, which is in great agreement with the Planck data. We also verify that the two independent constraints from the cosmic shear and the galaxy clustering+galaxy-galaxy lensing measurements are consistent with each other. To address baryonic feedback effects on small scales, we marginalize over a baryonic feedback parameter, which we are able to constrain with the DLS data alone and more tightly when combined with Planck data. The constrained value hints at the possibility that the AGN feedback in the current OWLS simulations might not be strong enough.

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The Joint analysis of galaxy clustering and weak lensing from the Deep Lens Survey to constrain cosmology and baryonic feedback

  • 윤미진;지명국
    • 천문학회보
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    • 제44권1호
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    • pp.79.2-79.2
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    • 2019
  • Based on three types of 2-point statistics (galaxy clustering, galaxy-galaxy lensing, and cosmic shear power spectra) from the Deep Lens Survey (DLS), we constrain cosmology and baryonic feedback. The DLS is a deep survey, so-called a precursor to LSST, reaching down to ~27th magnitude in BVRz' over 20 deg2. To measure the three power spectra, we choose two lens galaxy populations centered at z ~0.27 and 0.54 and two source galaxy populations centered at z ~0.64 and 1.1, with more than 1 million galaxies. We perform a number of consistency tests to confirm the reliability of the measurements. We calibrated photo-z estimation of the lens galaxies and validated the result with galaxy cross-correlation measurement. The B-mode signals, indicative of potential systematics, are found to be consistent with zero. The two cosmological results independently obtained from the cosmic shear and the galaxy clustering + galaxy-galaxy lensing measurements agree well with each other. Also, we verify that cosmological results between bright and faint sources are consistent. While there exist some weak lensing surveys showing a tension with Planck, the DLS constraint on S8 agrees nicely with the Planck result. Using the HMcode approach derived from the OWLS simulation, we constrain the strength of baryonic feedback. The DLS results hint at the possibility that the actual AGN feedback may be stronger than the one implemented in the current state-of-the-art simulations.

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Extended Kepler Grid-based System for Diabetes Study Workspace

  • Hazemi, Fawaz Al;Youn, Chan-Hyun
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2011년도 춘계학술발표대회
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    • pp.230-233
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    • 2011
  • Chronic disease is linked to patient's' lifestyle. Therefore, doctor has to monitor his/her patient over time. This may involve reviewing many reports, finding any changes, and modifying several treatments. One solution to optimize the burden is using a visualizing tool over time such as a timeline-based visualization tool where all reports and medicine are integrated in a problem centric and time-based style to enable the doctor to predict and adjust the treatment plan. This solution was proposed by Bui et. al. [2] to observe the medical history of a patient. However, there was limitation of studying the diabetes patient's history to find out what was the cause of the current development in patient's condition; moreover what would be the prediction of current implication in one of the diabetes' related factors (such as fat, cholesterol, or potassium). In this paper, we propose a Grid-based Interactive Diabetes System (GIDS) to support bioinformatics analysis application for diabetes diseases. GIDS used an agglomerative clustering algorithm as clustering correlation algorithm as primary algorithm to focus medical researcher in the findings to predict the implication of the undertaken diabetes patient. The algorithm was Chronological Clustering proposed by P. Legendre [11] [12].

Detection and Control of Variation Source for a Production Unit

  • Xu, Jichao;Akpolat, Hasan
    • International Journal of Quality Innovation
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    • 제4권1호
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    • pp.148-159
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    • 2003
  • Variation is the archenemy of quality. To reduce or control the variation in a complex production unit, firstly we need to identify the location of the root cause of the variation. This paper discusses the detection of variability and the techniques used for reduction of variation for a production unit consisting of many processes. In the first part of this paper, the background of variability detection in production systems is introduced which is then followed by a weighted network corresponding to correlation matrix of all processes. Based on the network and clustering criterion of maximum spanning tree, a classification of all processes is derived. Furthermore, the variation of each process in a class is determined by residual analysis. In the last part, the use of methods of robust design for the processes with a larger variability is discussed.

Fuzzy system construction based on Genetic Algorithms and fuzzy clustering

  • Kwak, Keun-Chang;Kim, Seoung-Suk;Ryu, Jeong-Woong;Chun, Myung-Geun
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.109.6-109
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    • 2002
  • In this paper, the scheme of fuzzy system construction using GA(genetic algorithm) and FCM(Fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. in the structure identification, input data is trans-formed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, the number of fuzzy rule is obtained by a given performance criterion. In the parameter identification, the premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this, one can systematically obtain optimal parameter and the v..

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Redshift Space Distortion on the Small Scale Clustering of Structure

  • Park, Hyunbae;Sabiu, Cristiano;Li, Xiao-dong;Park, Changbom;Kim, Juhan
    • 천문학회보
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    • 제42권2호
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    • pp.78.3-78.3
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    • 2017
  • The positions of galaxies in comoving Cartesian space varies under different cosmological parameter choices, inducing a redshift-dependent scaling in the galaxy distribution. The shape of the two-point correlation of galaxies exhibits a significant redshift evolution when the galaxy sample is analyzed under a cosmology differing from the true, simulated one. In our previous works, we can made use of this geometrical distortion to constrain the values of cosmological parameters governing the expansion history of the universe. This current work is a continuation of our previous works as a strategy to constrain cosmological parameters using redshift-invariant physical quantities. We now aim to understand the redshift evolution of the full shape of the small scale, anisotropic galaxy clustering and give a firmer theoretical footing to our previous works.

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