scholarly journals Curvature-Based Sparse Rule Base Generation for Fuzzy Interpolation Using Menger Curvature

2019 ◽  
pp. 53-65
Author(s):  
Zheming Zuo ◽  
Jie Li ◽  
Longzhi Yang
Keyword(s):  
Rule Base ◽  
Fuzzy Interpolation ◽  
Menger Curvature

scholarly journals Experience-based rule base generation and adaptation for fuzzy interpolation

2016 ◽  
Author(s):  
Jie Li ◽  
Hubert P. H. Shum ◽  
Xin Fu ◽  
Graham Sexton ◽  
Longzhi Yang
Keyword(s):  
Rule Base ◽  
Fuzzy Interpolation

Hierarchical Fuzzy Rule Interpolation and its Application for Hotels Location Selection

2016 ◽  
Vol 10 (1) ◽  
pp. 55-79 ◽  
Author(s):  
Yanling Jiang ◽  
Shangzhu Jin ◽  
Jun Peng
Keyword(s):  
Fuzzy Systems ◽  
Fuzzy Rule ◽  
Practical Investigations ◽  
Curse Of Dimensionality ◽  
Fuzzy Decision Making ◽  
Rule Base ◽  
Location Selection ◽  
Fuzzy Interpolation ◽  
Practical Applications ◽  
International Tourist

Fuzzy rule interpolation offers a useful means for enhancing the robustness of fuzzy models by making inference possible in systems of only a sparse rule base. However in practical applications, as the application domain of fuzzy systems expand to more complex ones, the curse of dimensionality problem of the conventional fuzzy systems became apparent, which makes the already challenging tasks such as inference and interpolation even more difficult. An initial idea of hierarchical fuzzy interpolation is presented in this paper. The proposed approach combines hierarchical fuzzy systems and fuzzy rule interpolation, to overcome the curse of dimensionality problem and the sparse rule base problem simultaneously. Hierarchical fuzzy interpolation is applicable to situations where a multiple multi-antecedent rules system needs to be reconstructed to a multi-layer fuzzy system and the sub-layer rules base is sparse. In order to demonstrate the potential of this approach, a hierarchical fuzzy decision making model for international tourist hotel location selection is provided in this paper. Criteria are acquired from literatures review and practical investigations for selecting the international tourist hotel location. These supportive systems can be directly presented to the tourists requesting a mechanism for selecting the most appropriate hotel, where lack enough information about the important indicators and factors. This model can also support the managers of hotels who are trying to make strategic decisions regarding the most optimized investments on the indicators of selecting a hotel. An empirical study for identifying the international tourist hotel location selection in Chongqing is conducted to demonstrate the computational results and effectiveness of the proposed methodology.

A Bidirectional Reasoning Based on Fuzzy Interpolation

2020 ◽  
Vol 12 (1) ◽  
pp. 1-14
Author(s):  
Shangzhu Jin
Keyword(s):  
Fuzzy System ◽  
Fuzzy Systems ◽  
Fuzzy Rule ◽  
Curse Of Dimensionality ◽  
Rule Base ◽  
Fuzzy Interpolation ◽  
Initial Idea ◽  
Conventional Methods ◽  
Hierarchical Fuzzy Systems

In order to deal with both the “curse of dimensionality” and the “sparse rule base” simultaneously, an initial idea of hierarchical bidirectional fuzzy interpolation is presented in this article, combining hierarchical fuzzy systems and forward/backward fuzzy rule interpolation. In particular, backward fuzzy interpolation can be employed to allow interpolation to be carried out when certain antecedents of observation variables are absent, whereas conventional methods do not work. Hierarchical bidirectional fuzzy interpolation is applicable to situations where a multiple multi-antecedent rules system needs to be reconstructed to a multi-layer fuzzy system and any sub-layer rule base is sparse. The implementation of this approach is based on fuzzy rule interpolative reasoning that utilities scale and move transformation. An illustrative example and application scenario are provided to demonstrate the efficacy of this proposed approach.

scholarly journals An extended Takagi–Sugeno–Kang inference system (TSK+) with fuzzy interpolation and its rule base generation

2017 ◽  
Vol 22 (10) ◽  
pp. 3155-3170 ◽  
Author(s):  
Jie Li ◽  
Longzhi Yang ◽  
Yanpeng Qu ◽  
Graham Sexton
Keyword(s):  
Rule Base ◽  
Inference System ◽  
Fuzzy Interpolation ◽  
Takagi Sugeno

Hierarchical Fuzzy Rule Interpolation and its Application for Hotels Location Selection

Fuzzy Systems ◽  
2017 ◽  
pp. 31-54
Author(s):  
Yanling Jiang ◽  
Shangzhu Jin ◽  
Jun Peng
Keyword(s):  
Fuzzy Systems ◽  
Fuzzy Rule ◽  
Curse Of Dimensionality ◽  
Fuzzy Decision Making ◽  
Rule Base ◽  
Location Selection ◽  
Fuzzy Interpolation ◽  
Practical Applications ◽  
International Tourist ◽  
Hierarchical Fuzzy Systems

Fuzzy rule interpolation offers a useful means for enhancing the robustness of fuzzy models by making inference possible in systems of only a sparse rule base. However in practical applications, as the application domain of fuzzy systems expand to more complex ones, the curse of dimensionality problem of the conventional fuzzy systems became apparent, which makes the already challenging tasks such as inference and interpolation even more difficult. An initial idea of hierarchical fuzzy interpolation is presented in this paper. The proposed approach combines hierarchical fuzzy systems and fuzzy rule interpolation, to overcome the curse of dimensionality problem and the sparse rule base problem simultaneously. Hierarchical fuzzy interpolation is applicable to situations where a multiple multi-antecedent rules system needs to be reconstructed to a multi-layer fuzzy system and the sub-layer rules base is sparse. In order to demonstrate the potential of this approach, a hierarchical fuzzy decision making model for international tourist hotel location selection is provided in this paper. Criteria are acquired from literatures review and practical investigations for selecting the international tourist hotel location. These supportive systems can be directly presented to the tourists requesting a mechanism for selecting the most appropriate hotel, where lack enough information about the important indicators and factors. This model can also support the managers of hotels who are trying to make strategic decisions regarding the most optimized investments on the indicators of selecting a hotel. An empirical study for identifying the international tourist hotel location selection in Chongqing is conducted to demonstrate the computational results and effectiveness of the proposed methodology.

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

Fuzzy Rule Base Design With Probabilistic Weights

2016 ◽  
Author(s):  
Leonardo G. Melo ◽  
Luís A. Lucas ◽  
Myriam R. Delgado
Keyword(s):  
Fuzzy Rule ◽  
Rule Base ◽  
Fuzzy Rule Base ◽  
Base Design

Using Gleams to Evaluate the Agricultural Waste Application Rule-Based Decision Support (AWARDS) Computer Program

1993 ◽  
Vol 28 (3-5) ◽  
pp. 625-634 ◽  
Author(s):  
D. A. Ford ◽  
A. P. Kruzic ◽  
R. L. Doneker
Keyword(s):  
Surface Water ◽  
Ground Water ◽  
Management Practices ◽  
Agricultural Waste ◽  
Rule Base ◽  
Rule Based ◽  
Pollutant Loading ◽  
Physical Features ◽  
To Receive ◽  
Complex Computer

AWARDS is a rule-based program that uses artificial intelligence techniques. It predicts the potential for fields receiving agricultural waste applications to degrade water quality. Input data required by AWARDS include the physical features, management practices, and crop nutrient needs for all fields scheduled to receive these nutrients. Based on a series of rules AWARDS analyzes the data and categorizes each field as acceptable or unacceptable for agricultural waste applications. The acceptable fields are then ranked according to their potential for pollutant loading. To evaluate the validity of the AWARDS field ranking system, it was compared to pollutant loading output from GLEAMS, a complex computer model. GLEAMS simulated the characteristics of each field ranked by AWARDS. Comparison of the AWARDS field ranking to the GLEAMS pollutant loading was favorable where ground water and both surface and ground water were to be protected and less favorable where surface water was to be protected. The rule base in AWARDS may need to be refined to provide more reasonable results where surface water is the resource of concern.

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