scholarly journals Rule Base Reduction Using Conflicting and Reinforcement Measures

2017 ◽  
pp. 129-137
Author(s):  
Luca Anzilli ◽  
Silvio Giove
Keyword(s):  
Rule Base ◽  
Reinforcement Measures

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.

scholarly journals A Fusion Prognostic Method for Remaining Useful Life Prediction Based on an Extended Belief Rule Base and Particle Filters

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Bincheng Wen ◽  
Mingqing Xiao ◽  
Guanghao Wang ◽  
Zhao Yang ◽  
Jianfeng Li ◽  
...  
Keyword(s):  
Life Prediction ◽  
Particle Filters ◽  
Remaining Useful Life ◽  
Rule Base ◽  
Belief Rule Base ◽  
Useful Life

A new approximate belief rule base expert system for complex system modelling

2021 ◽  
pp. 113558
Author(s):  
You Cao ◽  
Zhijie Zhou ◽  
Changhua Hu ◽  
Shuaiwen Tang ◽  
Jie Wang
Keyword(s):  
Complex System ◽  
Expert System ◽  
Rule Base ◽  
System Modelling ◽  
Belief Rule Base

New health-state assessment model based on belief rule base with interpretability

2021 ◽  
Vol 64 (7) ◽  
Author(s):  
Zhijie Zhou ◽  
You Cao ◽  
Guanyu Hu ◽  
Youmin Zhang ◽  
Shuaiwen Tang ◽  
...  
Keyword(s):  
State Assessment ◽  
Assessment Model ◽  
Rule Base ◽  
Health State ◽  
Model Based ◽  
Belief Rule Base

scholarly journals An Evolutionary Belief Rule-Based Clinical Decision Support System to Predict COVID-19 Severity under Uncertainty

2021 ◽  
Vol 11 (13) ◽  
pp. 5810
Author(s):  
Faisal Ahmed ◽  
Mohammad Shahadat Hossain ◽  
Raihan Ul Islam ◽  
Karl Andersson
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Experimental Result ◽  
Rule Base ◽  
Rule Based ◽  
Belief Rule Base

Accurate and rapid identification of the severe and non-severe COVID-19 patients is necessary for reducing the risk of overloading the hospitals, effective hospital resource utilization, and minimizing the mortality rate in the pandemic. A conjunctive belief rule-based clinical decision support system is proposed in this paper to identify critical and non-critical COVID-19 patients in hospitals using only three blood test markers. The experts’ knowledge of COVID-19 is encoded in the form of belief rules in the proposed method. To fine-tune the initial belief rules provided by COVID-19 experts using the real patient’s data, a modified differential evolution algorithm that can solve the constraint optimization problem of the belief rule base is also proposed in this paper. Several experiments are performed using 485 COVID-19 patients’ data to evaluate the effectiveness of the proposed system. Experimental result shows that, after optimization, the conjunctive belief rule-based system achieved the accuracy, sensitivity, and specificity of 0.954, 0.923, and 0.959, respectively, while for disjunctive belief rule base, they are 0.927, 0.769, and 0.948. Moreover, with a 98.85% AUC value, our proposed method shows superior performance than the four traditional machine learning algorithms: LR, SVM, DT, and ANN. All these results validate the effectiveness of our proposed method. The proposed system will help the hospital authorities to identify severe and non-severe COVID-19 patients and adopt optimal treatment plans in pandemic situations.

scholarly journals Knowledge-based Lean Six Sigma maintenance system for sustainable buildings

2017 ◽  
Vol 8 (1) ◽  
pp. 109-130 ◽  
Author(s):  
Jasim Aldairi ◽  
M.K. Khan ◽  
J. Eduardo Munive-Hernandez
Keyword(s):  
Conceptual Framework ◽  
Six Sigma ◽  
Research Work ◽  
Lean Six Sigma ◽  
Rule Base ◽  
Sustainable Buildings ◽  
Sustainable Building ◽  
Content Type ◽  
Environmentally Sustainable ◽  
Knowledge Based

Purpose This paper aims to develop a knowledge-based (KB) system for Lean Six Sigma (LSS) maintenance in environmentally sustainable buildings (Lean6-SBM). Design/methodology/approach The Lean6-SBM conceptual framework has been developed using the rule base approach of KB system and joint integration with gauge absence prerequisites (GAP) technique. A comprehensive literature review is given for the main pillars of the framework with a typical output of GAP analysis. Findings Implementation of LSS in the sustainable building maintenance context requires a pre-assessment of the organisation’s capabilities. A conceptual framework with a design structure is proposed to tackle this issue with the provision of an enhancing strategic and operational decision-making hierarchy. Research limitations/implications Future research work might consider validating this framework in other type of industries. Practical implications Maintenance activities in environmentally sustainable buildings must take prodigious standards into consideration, and, therefore, a robust quality assurance measure has to be integrated. Originality/value The significance of this research is to present a novel use of hybrid KB/GAP methodologies to develop a Lean6-SBM system. The originality and novelty of this approach will assist in identifying quality perspectives while implementing different maintenance strategies in the sustainable building context.

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