scholarly journals A New Approach to Comprehensive Assessing the Service Competitiveness of Motor Transport Enterprises Specializing in Municipal Passenger Transportation

TEM Journal ◽  
2020 ◽  
pp. 1126-1133
Author(s):  
Svitlana Moroz
Keyword(s):  
Principal Components ◽  
Group Composition ◽  
Expert Survey ◽  
New Approach ◽  
Motor Transport ◽  
Qualitative And Quantitative ◽  
Passenger Transportation ◽  
Method Of Principal Components

The author's method for assessing the level of the service competitiveness of motor transport enterprises specializing in municipal passenger transportation is developed and tested. A new approach to the formation of group composition and directly indicators of service competitiveness is offered. The author's method envisaged a combination of qualitative and quantitative aspects of the research, since the indicators' values were obtained as a result of the expert survey. During their elaboration the method of principal components was used to determine the weights of individual indicators and groups of the service competitiveness of motor transport enterprises.

Prediction indicators of the petroleum products quality using statistical methods

2021 ◽  
Author(s):  
Keyword(s):  
Petroleum Product ◽  
Principal Components ◽  
Autoregressive Model ◽  
Linear Models ◽  
Petroleum Products ◽  
Oil Refinery ◽  
Distributed Lag ◽  
Method Of Principal Components ◽  
Product Method

The possibility of the virtual analyzers models constructing of the petroleum products quality indicators for the atmospheric column of an oil refinery is considered. Comparison of linear models is carried out. It was found that more accurate and less costly are autoregressive models with a distributed lag. The use of such models at the facility improves the efficiency of obtaining information about the quality of petroleum products. Keywords virtual analyzers; autoregressive model; lag; factors; petroleum product; method of principal components; quality

A self-testing cloud model for multi-criteria group decision making

2016 ◽  
Vol 33 (6) ◽  
pp. 1767-1783 ◽  
Author(s):  
Ting-Cheng Chang ◽  
Hui Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Cloud Model ◽  
New Approach ◽  
Content Type ◽  
Qualitative And Quantitative ◽  
Composite Scale ◽  
Self Testing

Purpose – The purpose of this paper is to select the best scaling coefficient during the quantitative-qualitative conversion. Design/methodology/approach – Cloud model can describe the qualitative concept of randomness and fuzziness, achieve uncertain transition between qualitative and quantitative in the field of multi-criteria group decision and has been receiving widespread attention. This paper discusses scale conversion issues of the cloud model when evaluating qualitative information. In order to improve the accuracy of the evaluation on multi-attribute decision problems based on uncertainty of natural linguistic information, this paper proposes a method of self-testing cloud model based on a composite scale (with the exponential scale and the scale as a basis). Findings – Through experimental verification results show that under composite scale, the best suitable selection of can effectively improve the accuracy and reliability of decision results. Originality/value – This research presents a new approach to determine the suitable value for coefficient based on uncertain knowledge of natural multi-criteria group decision making, and gives concrete steps and examples. This method has positive significance to improve the quality of qualitative and quantitative conversion based on cloud model.

Optimized K-means (OKM) clustering algorithm for image segmentation

2012 ◽  
Vol 20 (3) ◽  
Author(s):  
F. Siddiqui ◽  
N. Mat Isa
Keyword(s):  
Clustering Algorithm ◽  
Local Minima ◽  
Initial Value ◽  
New Approach ◽  
Qualitative And Quantitative ◽  
Fitness Value ◽  
Segmented Images ◽  
Quantitative Analyses ◽  
Adjacent Cluster ◽  
Dead Centre

AbstractThis paper presents the optimized K-means (OKM) algorithm that can homogenously segment an image into regions of interest with the capability of avoiding the dead centre and trapped centre at local minima phenomena. Despite the fact that the previous improvements of the conventional K-means (KM) algorithm could significantly reduce or avoid the former problem, the latter problem could only be avoided by those algorithms, if an appropriate initial value is assigned to all clusters. In this study the modification on the hard membership concept as employed by the conventional KM algorithm is considered. As the process of a pixel is assigned to its associate cluster, if the pixel has equal distance to two or more adjacent cluster centres, the pixel will be assigned to the cluster with null (e. g., no members) or to the cluster with a lower fitness value. The qualitative and quantitative analyses have been performed to investigate the robustness of the proposed algorithm. It is concluded that from the experimental results, the new approach is effective to avoid dead centre and trapped centre at local minima which leads to producing better and more homogenous segmented images.

How We Can Use Multivariate Statistical Analysis to Predict Creasing of Fabrics

2014 ◽  
Vol 543-547 ◽  
pp. 1930-1933
Author(s):  
Katarína Zelová ◽  
Ludmila Fridrichová
Keyword(s):  
Statistical Analysis ◽  
Principal Components ◽  
Latent Variables ◽  
Analysis Method ◽  
Pca Analysis ◽  
Multivariate Statistical ◽  
Method Of Principal Components ◽  
Innovative Method ◽  
Component Loading

The creasing of textiles was evaluated by means of the innovative method of measuring the angle of recovery. Our aim is to find statistically significant features contributing to the determination of creasing materials. For this purpose, to identify the inner structures of data, the method of PCA analysis was used a method with latent variables. By means of PCA analysis (method of principal components) the original nine characteristics can be reduced to two latent variables, i.e. principal components. The structure and links among the examined features are characterized by methods like: Scree Plot, Score and component loading, Scatrerplot and Dendrogram.

scholarly journals Online Instructions: Problems and Potentials for the Teaching of English in Indonesia

2015 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Patrisius Istiarto Djiwandono
Keyword(s):  
Computer Technology ◽  
Reading Strategies ◽  
Online Teaching ◽  
Language Education ◽  
Online Course ◽  
New Approach ◽  
Qualitative And Quantitative ◽  
Technological Tools ◽  
Advanced Computer ◽  
General Profile

This paper reports the results of a survey of a one-semester online course for students majoring in Economics, Secretarial, Computer Technology, and Language Education. The teacher created online materials of reading strategies along with the assignment on www.blackboard, corn, and the students were instructed to access the materials, learn them independently, and do some self-evaluated reading assignments. Questionnaires were then distributed to see what obstacles had hampered their efforts in learning from online materials, as well as what advantages they gained from the new instructional approach. The qualitative and quantitative data culled from the questionnaires revealed potentials as well as some latent problems in carrying out an online teaching. The general profile that emerged was learners who were enthusiastic about learning through Internet and felt that the new approach had familiarized them with the future's technological tools, but who were mostly hampered by the lack of fund and facilities. These are discussed with special reference to the use of advanced computer technology in the teaching of English in Indonesia.

Sign in / Sign up

Export Citation Format

Share Document