• Title/Summary/Keyword: model rank

Search Result 607, Processing Time 0.03 seconds

Fuzzy Linear Regression Using Distribution Free Method (분포무관추정량을 이용한 퍼지회귀모형)

  • Yoon, Jin-Hee;Choi, Seung-Hoe
    • Communications for Statistical Applications and Methods
    • /
    • v.16 no.5
    • /
    • pp.781-790
    • /
    • 2009
  • This paper deals with a rank transformation method and a Theil's method based on an ${\alpha}$-level set of a fuzzy number to construct a fuzzy linear regression model. The rank transformation method is a simple procedure where the data are merely replaced with their corresponding ranks, and the Theil's method uses the median of all estimates of the parameter calculated from selected pairs of observations. We also consider two numerical examples to evaluate effectiveness of the fuzzy regression model using the proposed method and of another fuzzy regression model using the least square method.

Efficient Retrieval of Short Opinion Documents Using Learning to Rank (기계학습을 이용한 단문 오피니언 문서의 효율적 검색 기법)

  • Chang, Jae-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.13 no.4
    • /
    • pp.117-126
    • /
    • 2013
  • Recently, as Social Network Services(SNS), such as Twitter, Facebook, are becoming more popular, much research has been doing on opinion mining. However, current related researches are mostly focused on sentiment classification or feature selection, but there were few studies about opinion document retrieval. In this paper, we propose a new retrieval method of short opinion documents. Proposed method utilizes previous sentiment classification methodology, and applies several features of documents for evaluating the quality of the opinion documents. For generating the retrieval model, we adopt Learning-to-rank technique and integrate sentiment classification model to Learning-to-rank. Experimental results show that proposed method can be applied successfully in opinion search.

Wind velocity simulation of spatial three-dimensional fields based on autoregressive model

  • Gao, Wei-Cheng;Yu, Yan-Lei
    • Wind and Structures
    • /
    • v.11 no.3
    • /
    • pp.241-256
    • /
    • 2008
  • This paper adopts autoregressive (AR) model to simulate the wind velocity of spatial three-dimensional fields in accordance with the time and space dependent characteristics of the 3-D fields. Based on the built MATLAB programming, this paper discusses in detail the issues of the AR model deduced by matrix form in the simulation and proposes the corresponding solving methods: the over-relaxation iteration to solve the large sparse matrix equations produced by large number of degrees of freedom of structures; the improved Gauss formula to calculate the numerical integral equations which integral functions contain oscillating functions; the mixed congruence and central limit theorem of Lindberg-Levy to generate random numbers. This paper also develops a method of ascertaining the rank of the AR model. The numerical examples show that all those methods are stable and reliable, which can be used to simulate the wind velocity of all large span structures in civil engineering.

A Federated Multi-Task Learning Model Based on Adaptive Distributed Data Latent Correlation Analysis

  • Wu, Shengbin;Wang, Yibai
    • Journal of Information Processing Systems
    • /
    • v.17 no.3
    • /
    • pp.441-452
    • /
    • 2021
  • Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

An Analysis of Efficiency of Sea Food Manufacturing (수산식품 가공업의 효율성 분석)

  • Yoon, Sang-Ho;Park, Cheol-Hyung
    • The Journal of Fisheries Business Administration
    • /
    • v.46 no.2
    • /
    • pp.111-125
    • /
    • 2015
  • This study is to analyze the efficiency of Korean sea food manufacturing using Data Envelopment Analysis. Firstly, based on an output oriented traditional CCR, BCC model, the study estimated the efficiency scores. The average estimates of technical, pure technical, and scale efficiency turned out 0.6517, 0.7184, 0.9074 respectively, which are separated for 50 marine corporations. The 10 DMUs were efficient under CCR model while the 17 DMUs under BCC model. Also, the study suggested that the operating profit of the two output factors should be more increased relatively and averagely from the viewpoint of efficiency improvement. Secondly, super efficiency scores are estimated under super efficiency and SBM model. As a result, it came to be possible to distinguish and rank the efficiency of the efficient DMUs. The highest score was 4.2975 under Super-CCR, was 2.4947 under Super-BCC, was 2.7160 under SBM-Super-CCR, and was 1.5319 under SBM-Super-BCC model. The average estimates of super efficiency were 0.76 and 0.82 under Super-CCR and Super-BCC model respectively, and were 0.61 and 0.67 under SBM-Super-CCR and SBM-Super-BCC model. Finally, the study conducted a rank-sum test, Wilcoxon-Mann-Whitney test, to find a statistical significance of heterogeneity existing in efficiencies among the sample corporations. The result showed that there was a significant difference in average efficiency between Dried, Salted product manufacturing and Frozen product manufacturing under BCC-Super efficiency model at 10% level of significance. Furthermore, TOBIT model was applied to find out the potential factors that might influence the efficiency, Wilcoxonand the results showed debt and sales cost influenced all of the technical, pure technical, and scale efficiency, while net profit influenced only the technical efficiency.

Modified Weighting Model Rank Method for Improving the Performance of Real-Time Text-Independent Speaker Recognition System (실시간 문맥독립 화자인식 시스템의 성능향상을 위한 수정된 가중모델순위 결정방법)

  • Kim Min-Joung;Oh Se-Jin;Suk Su-Young;Chung Ho-Youl;Chung Hyun-Yeol
    • Proceedings of the Acoustical Society of Korea Conference
    • /
    • spring
    • /
    • pp.107-110
    • /
    • 2002
  • 현재까지 개발된 화자식별 시스템 중 가중모델순위(Weighting Model Rank; WMR)방법을 이용한 화자인식 시스템이 비교적 높은 인식성능을 나타내고 있다. WMR 방법은 각 화자에 대한 프레임 유사도의 순위에 따라 지수함수 가중치로 대치시키는 방법을 사용하고 있으나, 이 방법은 유사도 본래의 변별력이 전체 계산에서 고려되지 않는 문제가 있었다. 이를 해결하기 위해 본 논문에서는 각 화자의 프레임 유사도와 지수함수를 이용한 가중치를 곱한 값을 이용하여 전체 스코어를 계산하도록 하는 수정된 가중모델 순위방법(Modified Weighting Model Rank; MWMR)을 제안한다. 제안한 방법의 유효성을 확인하기 위하여 316명의 화자를 대상으로 하여 인식실험을 실시한 결과, 학습 프레임이 10,000일 경우, MWMR 방법에서 $98.1\%$의 화자 인식률을 얻어 WMR 방법에 비해 약 $2.0\%$의 향상된 인식결과를 보여 제안한 방법의 유효성을 확인할 수 있었다.

  • PDF

Comparison between Social Network Based Rank Discrimination Techniques of Data Envelopment Analysis: Beyond the Limitations (사회 연결망 분석 기반 자료포락분석 순위 결정 기법간 비교와 한계 극복 방안에 대한 연구)

  • Hee Jay Kang
    • Journal of Information Technology Services
    • /
    • v.22 no.1
    • /
    • pp.57-74
    • /
    • 2023
  • It has been pointed out as a limitation that the rank of some efficient DMUs(decision making units) cannot be discriminated due to the relativity nature of efficiency measured by DEA(data envelopment analysis), comparing the production structure. Recently, to solve this problem, a DEA-SNA(social network analysis) model that combines SNA techniques with data envelopment analysis has been studied intensively. Several models have been proposed using techniques such as eigenvector centrality, pagerank centrality, and hypertext induced topic selection(HITS) algorithm, but DMUs that cannot be ranked still remain. Moreover, in the process of extracting latent information within the DMU group to build effective network, a problem that violates the basic assumptions of the DEA also arises. This study is meaningful in finding the cause of the limitations by comparing and analyzing the characteristics of the DEA-SNA model proposed so far, and based on this, suggesting the direction and possibility to develop more advanced model. Through the results of this study, it will be enable to further expand the field of research related to DEA.

Low-rank Coal Char Gasification Research with Mixed Catalysts at Fixed Reactor (고정층 반응기에서의 저등급 석탄 혼합촉매가스화 반응특성)

  • An, Seung Ho;Park, Ji Yun;Jin, Gyoung Tae;Rhee, Young Woo
    • Korean Chemical Engineering Research
    • /
    • v.55 no.1
    • /
    • pp.99-106
    • /
    • 2017
  • In this study, mixed catalytic char gasification of Indonesia low-rank coal Kideco was investigated under nitrogen atmosphere and isothermal conditions at a fixed reactor. The effects of the temperature were investigated at various temperature (700, 750, 800, $850^{\circ}C$). The effects of blend ratio of catalysts ($K_2CO_3$, Ni) were investigated with different blend ratios (1:9, 3:7, 5:5, 7:3 and 9:1). The sample was prepared by mixing with $K_2CO_3$ physically and by ionexchange method with Ni. The data from thermogravimetric analyzer and gas chromatography were applied to four gassolid reaction kinetic models including shrinking core model, volumetric reaction model, random pore model and modified volumetric reaction model.

Block Sparse Low-rank Matrix Decomposition based Visual Defect Inspection of Rail Track Surfaces

  • Zhang, Linna;Chen, Shiming;Cen, Yigang;Cen, Yi;Wang, Hengyou;Zeng, Ming
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.13 no.12
    • /
    • pp.6043-6062
    • /
    • 2019
  • Low-rank matrix decomposition has shown its capability in many applications such as image in-painting, de-noising, background reconstruction and defect detection etc. In this paper, we consider the texture background of rail track images and the sparse foreground of the defects to construct a low-rank matrix decomposition model with block sparsity for defect inspection of rail tracks, which jointly minimizes the nuclear norm and the 2-1 norm. Similar to ADM, an alternative method is proposed in this study to solve the optimization problem. After image decomposition, the defect areas in the resulting low-rank image will form dark stripes that horizontally cross the entire image, indicating the preciselocations of the defects. Finally, a two-stage defect extraction method is proposed to locate the defect areas. The experimental results of the two datasets show that our algorithm achieved better performance compared with other methods.

Efficient Link Adaptation Scheme using Precoding for LTE-Advanced Uplink MIMO (LTE-Advanced에서 프리코딩에 의한 효율적인 상향링크 적응 방식)

  • Park, Ok-Sun;Ahn, Jae-Min
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.36 no.2B
    • /
    • pp.159-167
    • /
    • 2011
  • LTE-Advanced system requires uplink multi-antenna transmission in order to achieve the peak spectral efficiency of 15bps/Hz. In this paper, the uplink MIMO system model for the LTE-Advanced is proposed and an efficient link adaptation shceme using precoding is considered providing error rate reduction and system capacity enhancement. In particular, the proposed scheme determines a transmission rank by selecting the optimal wideband precoding matrix, which is based on the derived signal-to-interference and noise ratio (SINR) for the minimum mean squared error (MMSE) receivers of $2{\times}4$ multiple input multiple output (MIMO). The proposed scheme is verified by simulation with a practical MIMO channel model. The simulation results of average block-error-rate(BLER) reflect that the gain due to the proposed rank adapted transmission over full-rank transmission is evident particularly in the case of lower modulation and coding scheme (MCS) and high mobility, which means the severe channel fading environment.