Exploring the Logic and Developing New Classification Methods in Attribute Hierarchy Model

2009 ◽  
Author(s):  
Mengmeng Mao ◽  
Shuliang Ding
Keyword(s):  
Classification Methods ◽  
New Classification ◽  
Hierarchy Model ◽  
Attribute Hierarchy

scholarly journals A Grey Multi-Level Evaluation of Industrial Park Ecology Based on a Coefficient of Variation-Attribute Hierarchy Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1805
Author(s):  
Baolin Qiu ◽  
Dongkun Luo
Keyword(s):  
Technological Development ◽  
Theory And Practice ◽  
Industrial Park ◽  
Policy Management ◽  
Good Level ◽  
Industrial Parks ◽  
Hierarchy Model ◽  
Attribute Hierarchy ◽  
Multi Level ◽  
Ecological Construction

China entered a new era, and the construction of an ecological civilization and green development has been raised to a new strategic height. As the lifeblood of the national economy, industrial parks significantly contribute to economic growth. However, they also generate significant pollution, damaging the ecological environment. It is urgent to ecologically transform traditional industrial parks. This requires identifying methods to correctly and objectively evaluate the ecological level of industrial parks, and provide ecological construction proposals for the government and industrial parks. In this study, the comprehensive evaluation weight was determined by introducing a variation coefficient and an Attribute Hierarchy Model (AHM). The ecological level of four representative eco-industrial parks was then quantitatively evaluated using a grey multi-level evaluation method. The ecological construction level of the four industrial parks was as follows. The Tianjin Economic-Technological Development Area (TEDA) was rated at a “very good” level; and the Suzhou industrial park, Dalian economic and technological development zone, and Fushun mining group were rated at a “good” level. Six dimensions were studied. Of these, policy management had the highest weight, and the total weight of policy management and economic development approached 50%. The result shows that industrial parks can attract innovative enterprises and talents through the policy guidance of local government to improve the level of green innovation technology and cleaner production technology. Then, the ecological level of the industrial parks will be improved. This study enriched the theory and practice of ecological evaluation of industrial parks and provided a reference for the ecological construction of traditional industrial parks.

P1-177: Neuropsychiatric inventory for Alzheimer's disease and mild cognitive impairment's patients with new classification methods

2009 ◽  
Vol 5 (4S_Part_8) ◽  
pp. P228-P229
Author(s):  
Taewan Kim ◽  
Jinsuk Kim ◽  
Jangjun Lee ◽  
Jongwhan Choi ◽  
Sangwon Park ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Classification Methods ◽  
Neuropsychiatric Inventory ◽  
New Classification

scholarly journals Update (2.0) to LyapXool: Eigenpairs and new classification methods

SoftwareX ◽  
2020 ◽  
Vol 12 ◽  
pp. 100616
Author(s):  
Carlos Argáez ◽  
Peter Giesl ◽  
Sigurdur Freyr Hafstein
Keyword(s):  
Classification Methods ◽  
New Classification

Some new classification methods for hyperspectral remote sensing

2006 ◽  
Author(s):  
Pei-jun Du ◽  
Yun-hao Chen ◽  
Simon Jones ◽  
Jelle G. Ferwerda ◽  
Zhi-jun Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Remote Sensing ◽  
Classification Methods ◽  
New Classification

scholarly journals An attribute-based classification by threshold to enhance the data matching process

2019 ◽  
Vol 17 (4) ◽  
Author(s):  
Maria Del Pilar Angeles ◽  
Carlos G. Ortiz Monreal
Keyword(s):  
Unsupervised Classification ◽  
Classification Methods ◽  
New Classification ◽  
Data Matching ◽  
Matching Process ◽  
Disparate Data ◽  
And Performance ◽  
Business Competitiveness

The problem of detection and classification of extensional inconsistencies during data integration of disparate data sources affects business competitiveness. A number of classification methods have been utilized until now, but there still some work to do in terms of effectiveness and performance. The paper shows the proposal, implementation, and evaluation of a new classification algorithm called Attribute-based Classification by Threshold that overcomes the disadvantages of the Threshold-based Classification. We have carried aout an evaluation of quality of the data matching process by comparing Threshold-based Classification, Farthest First and K-means against the proposed algorithm. The Attribute-based Classification by Threshold has a better performance than the rest of the unsupervised classification methods.

scholarly journals Challenge to Vaccine Side Effect Evaluation and Reporting Models:A New Classification Methods

2021 ◽  
Author(s):  
Jianqing Wu
Keyword(s):  
Side Effects ◽  
Side Effect ◽  
New Method ◽  
Classification Methods ◽  
Effect Evaluation ◽  
New Classification ◽  
Potential Risks

An article concerns potential risks of mass vaccines for the COVID-19 disease. It explains why current research models cannot find multiple side effects. In addition, the authors also propose a new method for classifying deaths caused by vaccines.

scholarly journals Combined Regularized Discriminant Analysis and Swarm Intelligence Techniques for Gait Recognition

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6794
Author(s):  
Tomasz Krzeszowski ◽  
Krzysztof Wiktorowicz
Keyword(s):  
Discriminant Analysis ◽  
Swarm Intelligence ◽  
Hybrid Methods ◽  
Gait Recognition ◽  
Classification Methods ◽  
Grey Wolf ◽  
New Classification ◽  
Grey Wolf Optimization ◽  
Swarm Optimization ◽  
Whale Optimization

In the gait recognition problem, most studies are devoted to developing gait descriptors rather than introducing new classification methods. This paper proposes hybrid methods that combine regularized discriminant analysis (RDA) and swarm intelligence techniques for gait recognition. The purpose of this study is to develop strategies that will achieve better gait recognition results than those achieved by classical classification methods. In our approach, particle swarm optimization (PSO), grey wolf optimization (GWO), and whale optimization algorithm (WOA) are used. These techniques tune the observation weights and hyperparameters of the RDA method to minimize the objective function. The experiments conducted on the GPJATK dataset proved the validity of the proposed concept.

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