The Measurement of Relationships between Regional Structure and its Evolution

1980 ◽  
Vol 12 (1) ◽  
pp. 3-20
Author(s):  
H Beguin
Keyword(s):  
Component Analysis ◽  
Canonical Analysis ◽  
Regional Structure ◽  
Good Tool ◽  
Methodological Problems ◽  
Simultaneous Use

Using a regional case study, the paper investigates some methodological problems concerning the measure of the relationships between two sets of variables. Canonical analysis seems a good tool, but discussion of its advantages and drawbacks shows it is not fully satisfactory. Other methods are tested and their efficiency discussed: Regression, joint-set component analysis, canonical-subspace interpretation by communalities, component-based redundancy. In conclusion, simultaneous use of canonical analysis and other methods is recommended since their results appear complementary.

scholarly journals Improved Process Monitoring Scheme Using Multi-Scale Independent Component Analysis

2021 ◽  
Author(s):  
K Ramakrishna Kini ◽  
Muddu Madakyaru
Keyword(s):  
Fault Detection ◽  
Independent Component Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
Noisy Environment ◽  
Process Data ◽  
Multi Scale ◽  
Efficient Information ◽  
Non Gaussian

AbstractThe task of fault detection is crucial in modern chemical industries for improved product quality and process safety. In this regard, data-driven fault detection (FD) strategy based on independent component analysis (ICA) has gained attention since it improves monitoring by capturing non-gaussian features in the process data. However, presence of measurement noise in the process data degrades performance of the FD strategy since the noise masks important information. To enhance the monitoring under noisy environment, wavelet-based multi-scale filtering is integrated with the ICA model to yield a novel multi-scale Independent component analysis (MSICA) FD strategy. One of the challenges in multi-scale ICA modeling is to choose the optimum decomposition depth. A novel scheme based on ICA model parameter estimation at each depth is proposed in this paper to achieve this. The effectiveness of the proposed MSICA-based FD strategy is illustrated through three case studies, namely: dynamic multi-variate process, quadruple tank process and distillation column process. In each case study, the performance of the MSICA FD strategy is assessed for different noise levels by comparing it with the conventional FD strategies. The results indicate that the proposed MSICA FD strategy can enhance performance for higher levels of noise in the data since multi-scale wavelet-based filtering is able to de-noise and capture efficient information from noisy process data.

Application of the principal component analysis on geochemical data: a case study in the basement complex of Southern Ilesa area, Nigeria

2010 ◽  
Vol 4 (1-2) ◽  
pp. 239-247 ◽  
Author(s):  
Emmanuel A. Ariyibi ◽  
Samuel L. Folami ◽  
Bankole D. Ako ◽  
Taye R. Ajayi ◽  
Adebowale O. Adelusi
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Geochemical Data ◽  
Basement Complex

scholarly journals Primary components in shaping koperasi masjid’s participation level: Employing a principle component analysis approach

2018 ◽  
Vol 31 (3) ◽  
pp. 318
Author(s):  
Fitriani Fitriani ◽  
Sudiyo Sudiyo ◽  
Dayang Berliana ◽  
Evi Yuniarti
Keyword(s):  
Factor Analysis ◽  
Strong Correlation ◽  
Principal Component ◽  
Component Analysis ◽  
Primary Factor ◽  
Analysis Approach ◽  
Second Primary ◽  
Study Approach ◽  
Participation Level

Koperasi masjid present themselves as a part of muamalah through Sharia economic facilitation. This study was conducted to analyse the cooperative members’ participation level in relation to the implementation of a cooperative business program. A survey using a case study approach was conducted at koperasi Masjid Hafshotul Iman, Masjid Taqwa and Masjid Darul HikmahThe survey employed a purposive sampling method with the participation of the cooperative’s management (chairman, secretary, and treasurer) and the masjid’s members. Ten respondents were purposively chosen from each mosque and a total 30 respondents were acquired. The distributed questionnaire was a closed one, measured with a Likert scale. The results were analysed using factor analysis and the Principal Component Analysis approach (PCA). Based on the results of the factor analysis, the members’ participation level in cooperative service can be classified into three primary factors. Some of the variables displayed a strong correlation with Factor 1, namely motivation, management performance, RAT performance, and supervisor performance. The second primary factor was formed by activeness in participating in cooperative activities. Lastly, the third primary factor encompassed three variables with a strong correlation, namely age, education, and membership duration.

Multimodal contribution to speech perception revealed by independent component analysis: a single-sweep EEG case study

2001 ◽  
Vol 10 (3) ◽  
pp. 349-353 ◽  
Author(s):  
Daniel E. Callan ◽  
Akiko M. Callan ◽  
Christian Kroos ◽  
Eric Vatikiotis-Bateson
Keyword(s):  
Speech Perception ◽  
Independent Component Analysis ◽  
Component Analysis ◽  
Independent Component

scholarly journals Groundwater Quality Assessment: An Improved Approach to K-Means Clustering, Principal Component Analysis and Spatial Analysis: A Case Study

Water ◽  
2018 ◽  
Vol 10 (4) ◽  
pp. 437 ◽  
Author(s):  
Ana Marín Celestino ◽  
Diego Martínez Cruz ◽  
Elena Otazo Sánchez ◽  
Francisco Gavi Reyes ◽  
David Vásquez Soto
Keyword(s):  
Principal Component Analysis ◽  
Spatial Analysis ◽  
Groundwater Quality ◽  
Quality Assessment ◽  
Principal Component ◽  
Component Analysis ◽  
Groundwater Quality Assessment
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