A NEW APPROACH TO LEARNING LINGUISTIC CONTROL RULES

2000 ◽  
Vol 08 (01) ◽  
pp. 21-43 ◽  
Author(s):  
J. F. BALDWIN ◽  
J. LAWRY
Keyword(s):  
Rule Base ◽  
Linguistic Variables ◽  
Data Set ◽  
New Approach ◽  
Approach To Learning ◽  
Control Rules ◽  
System A ◽  
Id3 Algorithm ◽  
On Line ◽  
Linguistic Control

The mass assignment ID3 (MA-ID3) algorithm for generating linguistic decision trees is introduced together with the mass assignment semantics for linguistic variables. The potential of this algorithm for learning control rules is illustrated by means of the Van de Pol system. A data set of control paths is generated using an existing on-line controller. This is then used to generate a set of quantified linguistic control rules. The effectiveness and robustness of this rule-base is then demonstrated.

A new approach for tuning control rule based on hedge algebras theory and application in structural vibration control

2020 ◽  
pp. 107754632096430
Author(s):  
Hai-Le Bui ◽  
Quy-Cao Tran
Keyword(s):  
Vibration Control ◽  
Control Process ◽  
Structural Vibration ◽  
Rule Base ◽  
Control Performance ◽  
Rule Based ◽  
New Approach ◽  
Structural Vibration Control ◽  
Control Rules ◽  
The Impact

The hedge algebras theory has the potential to make significant applications in the field of computational intelligence. The purpose of the present study is to improve the control performance of the hedge algebras–based controller by tuning its control rules and apply the hedge algebras–based controller using the tuned rule base in vibration control of structures. The authors propose a “tuning coefficient” to express the impact of each rule of the controller in the control process. These control rules are adjusted by optimizing the above tuning coefficient. The tuned controller is then used to reduce the dynamic response of structures subjected to different excitations. The adjusted rule base is more appropriate for the model to be controlled, and it allows enhancing the control performance of the system. The proposed approach is uncomplicated and transparent, and it allows preserving the monotonous feature of the rule base.

A New Approach for the Analysis of Mixture Toxicity Data

1992 ◽  
Vol 26 (9-11) ◽  
pp. 2345-2348 ◽  
Author(s):  
C. N. Haas
Keyword(s):  
Quantitative Analysis ◽  
Mixture Toxicity ◽  
New Method ◽  
Metal Exposure ◽  
Positive Interactions ◽  
Toxicity Data ◽  
Data Set ◽  
New Approach ◽  
Negative Interactions

A new method for the quantitative analysis of multiple toxicity data is described and illustrated using a data set on metal exposure to copepods. Positive interactions are observed for Ni-Pb and Pb-Cr, with weak negative interactions observed for Ni-Cr.

A nano-composite resist system: A new approach to nanometer pattern fabrication

1997 ◽  
Vol 35 (1-4) ◽  
pp. 113-116 ◽  
Author(s):  
T. Ishii ◽  
H. Nozawa ◽  
T. Tamamura
Keyword(s):  
Nano Composite ◽  
New Approach ◽  
System A ◽  
Nanometer Pattern

Pl@ntwood: A Computer-Assisted Identification Tool for 110 species of amazon trees based on wood Anatomical Features

IAWA Journal ◽  
2011 ◽  
Vol 32 (2) ◽  
pp. 221-232 ◽  
Author(s):  
Carolina Sarmiento ◽  
Pierre Détienne ◽  
Christine Heinz ◽  
Jean-François Molino ◽  
Pierre Grard ◽  
...  
Keyword(s):  
Tree Species ◽  
Tropical Species ◽  
Computer Assisted ◽  
Accurate Identification ◽  
Anatomical Features ◽  
System A ◽  
Microscopic Features ◽  
On Line ◽  
User Friendly ◽  
Identification Tool

Sustainable management and conservation of tropical trees and forests require accurate identification of tree species. Reliable, user-friendly identification tools based on macroscopic morphological features have already been developed for various tree floras. Wood anatomical features provide also a considerable amount of information that can be used for timber traceability, certification and trade control. Yet, this information is still poorly used, and only a handful of experts are able to use it for plant species identification. Here, we present an interactive, user-friendly tool based on vector graphics, illustrating 99 states of 27 wood characters from 110 Amazonian tree species belonging to 34 families. Pl@ntWood is a graphical identification tool based on the IDAO system, a multimedia approach to plant identification. Wood anatomical characters were selected from the IAWA list of microscopic features for hardwood identification, which will enable us to easily extend this work to a larger number of species. A stand-alone application has been developed and an on-line version will be delivered in the near future. Besides allowing non-specialists to identify plants in a user-friendly interface, this system can be used with different purposes such as teaching, conservation, management, and selftraining in the wood anatomy of tropical species.

Nasal Tramadol delivery system: A new approach for improved pain therapy

2011 ◽  
Vol 5 (S2) ◽  
pp. 449-452 ◽  
Author(s):  
Shaher Duchi ◽  
Elka Touitou ◽  
Lorenzo Pradella ◽  
Francesco Marchini ◽  
Denize Ainbinder
Keyword(s):  
Delivery System ◽  
Pain Therapy ◽  
New Approach ◽  
System A

A New Approach to Machinery Monitoring and Diagnostics Using Self-Organizing Maps

1995 ◽  
Author(s):  
Siyu Zhang ◽  
R. Ganesan ◽  
T. S. Sankar
Keyword(s):  
Neural Network ◽  
Service Life ◽  
Trend Analysis ◽  
New Approach ◽  
Machine System ◽  
Network Algorithm ◽  
On Line ◽  
Neural Network Algorithm ◽  
Monitoring And Diagnostics ◽  
Self Organizing

Abstract The problem of estimating an unknown multivariate function from on-line vibration measurements, for determining the conditions of a machine system and for estimating its service life is considered. This problem is formulated into a multiple-index based trend analysis problem and the corresponding indices for trend analysis are extracted from the on-line vibration data. Selection of these indices is based on the simultaneous consideration of commonly-observed faults or malfunctions in the machine system being monitored. A neural network algorithm that has been developed by the present authors for multiple-index based regression is adapted to perform the trend analysis of a machine system. Applications of this neural network algorithm to the condition monitoring and life estimation of both a bearing system as well as a gearbox are fully demonstrated. The efficiency and computational supremacy of the new algorithm are established through comparing with the performance of Self-Organizing Mapping (SOM) and Constrained Topological Mapping (CTM) algorithms. Further, the usefulness of multiple-index based trend analysis in precisely predicting the condition and service life of a machine system is clearly demonstrated. Using on-line vibration signal to constitute the set of variables for trend analysis, and employing the newly-developed self-organizing neural algorithm for performing the trend analysis, a new approach is developed for machinery monitoring and diagnostics.

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