Permeability prediction in shaly formations: The fuzzy modeling approach

Geophysics ◽  
2002 ◽  
Vol 67 (3) ◽  
pp. 817-829 ◽  
Author(s):  
Jose Finol ◽  
Xu‐Dong D. Jing
Keyword(s):  
Clustering Algorithm ◽  
Fuzzy Inference ◽  
Fuzzy Rule ◽  
Learning Task ◽  
Well Log ◽  
Rule Based ◽  
Maracaibo Basin ◽  
Core Permeability ◽  
Rule Based Approach

This paper shows how fuzzy rule‐based systems help predict permeability in sedimentary rocks using well‐log responses. The fuzzy rule‐based approach represents a global nonlinear relationship between permeability and a set of input log responses as a smooth concatenation of a finite family of flexible local submodels. The fuzzy inference rules expressing the local input‐output relationships are obtained automatically from a set of observed measurements using a fuzzy clustering algorithm. This approach simplifies the process of constructing fuzzy systems without much computation effort. The benefits of the methodology are demonstrated with a case study in the Lake Maracaibo basin, Venezuela. Special core analyses from three early development wells provide the data for the learning task. Core permeability and well‐log data from a fourth well provide the basis for model validation. Numerical simulation results show that the fuzzy system is an improvement over conventional empirical methods in terms of predictive capability.

Fuzzy rule-based motion controller for an autonomous mobile robot

Robotica ◽  
1989 ◽  
Vol 7 (1) ◽  
pp. 37-42 ◽  
Author(s):  
M. Kemal Ciliz ◽  
Can Isik
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Rule ◽  
Hierarchical Structures ◽  
Mobile Systems ◽  
Real Time Control ◽  
Rule Based ◽  
Sensory Data ◽  
Time Control ◽  
Control Command ◽  
Rule Based Approach

SUMMARYIntelligent control of mobile systems allows for hierarchical structures that utilize sensory data with various levels of accuracy. This paper discusses a rule-based approach for the control problem. The assumed inexactness in world description is represented by fuzzy memberships, and the state space is discretized into a linguistic vocabulary. Fuzzy motion control rules that have been experimentally derived, are then used in a fuzzy inference mechanism to give the final control command to robot actuators. Finally, the developed algorithm is tested for real-time control applications.

MRI Brain Tumor Image Analysis Using Fuzzy Rule based Approach

2019 ◽  
Vol 50 (2) ◽  
pp. 98-112 ◽  
Author(s):  
KALYAN KUMAR JENA ◽  
SASMITA MISHRA ◽  
SAROJANANDA MISHRA ◽  
SOURAV KUMAR BHOI ◽  
SOUMYA RANJAN NAYAK
Keyword(s):  
Image Analysis ◽  
Brain Tumor ◽  
Fuzzy Rule ◽  
Rule Based ◽  
Mri Brain ◽  
Rule Based Approach

scholarly journals Approximate reasoning with fuzzy rule interpolation: background and recent advances

2021 ◽  
Author(s):  
Fangyi Li ◽  
Changjing Shang ◽  
Ying Li ◽  
Jing Yang ◽  
Qiang Shen
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Rule ◽  
Approximate Reasoning ◽  
Rule Based ◽  
Reasoning Systems ◽  
Significant Interest ◽  
Recent Developments ◽  
Rule Bases ◽  
The Given ◽  
Computing Approach

AbstractApproximate reasoning systems facilitate fuzzy inference through activating fuzzy if–then rules in which attribute values are imprecisely described. Fuzzy rule interpolation (FRI) supports such reasoning with sparse rule bases where certain observations may not match any existing fuzzy rules, through manipulation of rules that bear similarity with an unmatched observation. This differs from classical rule-based inference that requires direct pattern matching between observations and the given rules. FRI techniques have been continuously investigated for decades, resulting in various types of approach. Traditionally, it is typically assumed that all antecedent attributes in the rules are of equal significance in deriving the consequents. Recent studies have shown significant interest in developing enhanced FRI mechanisms where the rule antecedent attributes are associated with relative weights, signifying their different importance levels in influencing the generation of the conclusion, thereby improving the interpolation performance. This survey presents a systematic review of both traditional and recently developed FRI methodologies, categorised accordingly into two major groups: FRI with non-weighted rules and FRI with weighted rules. It introduces, and analyses, a range of commonly used representatives chosen from each of the two categories, offering a comprehensive tutorial for this important soft computing approach to rule-based inference. A comparative analysis of different FRI techniques is provided both within each category and between the two, highlighting the main strengths and limitations while applying such FRI mechanisms to different problems. Furthermore, commonly adopted criteria for FRI algorithm evaluation are outlined, and recent developments on weighted FRI methods are presented in a unified pseudo-code form, easing their understanding and facilitating their comparisons.

scholarly journals A Novel Rules Based Approach for Estimating Software Birthmark

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Shah Nazir ◽  
Sara Shahzad ◽  
Sher Afzal Khan ◽  
Norma Binti Alias ◽  
Sajid Anwar
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Rule ◽  
New Technique ◽  
License Agreement ◽  
Rule Based ◽  
Software Birthmark ◽  
A New Technique

Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark.

Transit Shift Response Analysis Through Fuzzy Rule Based-Choice Model: A Case Study of Indian Metropolitan City

2017 ◽  
Vol 3 (1) ◽  
Author(s):  
Ashu S. Kedia ◽  
D. Sowjanya ◽  
P. S. Salini ◽  
M. Jabeena ◽  
Bhimaji Krishnaji Katti
Keyword(s):  
Choice Model ◽  
Fuzzy Rule ◽  
Response Analysis ◽  
Rule Based ◽  
Metropolitan City ◽  
Shift Response

Construction of H5-Index for Conference Ranking Indicator and its Correlation to ERA

2021 ◽  
Vol 20 (01) ◽  
pp. 2150011
Author(s):  
Worapan Kusakunniran ◽  
Thearith Ponn ◽  
Nuttapol Boonsom ◽  
Suwimol Wahakit ◽  
Kittikhun Thongkanchorn
Keyword(s):  
Correlation Analysis ◽  
Quality Assessment ◽  
Computer Science ◽  
Strong Correlation ◽  
Moderate Correlation ◽  
Data Cleansing ◽  
Rule Based ◽  
Ranking Systems ◽  
Rule Based Approach

This paper develops the Scopus H5-Index rankings, using the field of computer science as a case study. The challenge begins with the inconsistency of conference names. The rule-based approach is invented to automatically clean up duplicate conferences and assign unique pseudo ID for each conference. This data cleansing process is applied on conference names retrieved from both Scopus and ERA/CORE, in order to share common pseudo IDs for the sake of correlation analysis. The proposed data cleansing process is validated using ERA 2010 and CORE 2018 as references and reports the very small errors of 0.6% and 0.4%, respectively. Then, the Scopus H5-Index 2006–2010 and Scopus H5-Index 2014–2018 rankings are constructed and compared with the existing ERA 2010 and CORE 2018 rankings, respectively. The results show that the correlation within the Scopus H5-Index rankings (i.e. Scopus H5-Index 2006–2010 and Scopus H5-Index 2014–2018) is at the top of the moderate correlation band, where the correlation within the ERA/CORE rankings (ERA 2010 and CORE 2018) is at the top of the strong correlation band. While the correlations across ranking systems (i.e. Scopus H5-Index 2006–2010 vs. ERA 2010, and Scopus H5-Index 2014–2018 vs. CORE 2018) are at the bottom and middle of the moderate correlation band. It can be said that the quality assessment using the Scopus H5-Index ranking is more dynamic and quickly up-to-date when compared with the ERA/CORE ranking. Also, these two ranking systems are moderately correlated with each other for both periods of 2010 and 2018.

Assessing flood vulnerability using a rule-based fuzzy system

2012 ◽  
Vol 66 (8) ◽  
pp. 1766-1773 ◽  
Author(s):  
J. Yazdi ◽  
S. A. A. S. Neyshabouri
Keyword(s):  
Fuzzy Rule ◽  
Vulnerability Analysis ◽  
Human Knowledge ◽  
Small Watershed ◽  
Flood Vulnerability ◽  
Rule Based ◽  
Rule Based System ◽  
Vulnerability Map ◽  
Flood Prone Areas

Population growth and urbanization in the last decades have increased the vulnerability of properties and societies in flood-prone areas. Vulnerability analysis is one of the main factors used to determine the necessary measures of flood risk reduction in floodplains. At present, the vulnerability of natural disasters is analyzed by defining the various physical and social indices. This study presents a model based on a fuzzy rule-based system to address various ambiguities and uncertainties from natural variability, and human knowledge and preferences in vulnerability analysis. The proposed method is applied for a small watershed as a case study and the obtained results are compared with one of the index approaches. Both approaches present the same ranking for the sub-basin's vulnerability in the watershed. Finally, using the scores of vulnerability in different sub-basins, a vulnerability map of the watershed is presented.

Fuzzy-Rule Based Adaptive Data Warehouse

2012 ◽  
Vol 3 (1) ◽  
pp. 47-65 ◽  
Author(s):  
Rajdev Tiwari ◽  
Anubhav Tiwari ◽  
Manu Pratap Singh
Keyword(s):  
Decision Making ◽  
Fuzzy Inference ◽  
Knowledge Workers ◽  
Fuzzy Rule ◽  
Data Warehouses ◽  
Large Reservoir ◽  
Inference System ◽  
Rule Based ◽  
Neuro Fuzzy ◽  
New Generation

Data Warehouses (DWs) are aimed to empower the knowledge workers with information and knowledge which helps them in decision making. Technically, the DW is a large reservoir of integrated data that does not provide the intelligence or the knowledge demanded by users. The burden of data analysis and extraction of information and knowledge from integrated data still lies upon the analyst’s shoulder. The overhead of analysts can be taken off by architecting a new generation data warehouses systems those shall be capable of capturing, organizing and representing knowledge along with the data and information in it. This new generation DW may be called as Knowledge Warehouse (KW) shall exhibit decision making capabilities themselves and can also supplement the Decision Support Systems (DSS) in making decisions quickly and effortlessly. This paper proposes and simulates a fuzzy-rule based adaptive knowledge warehouse with capabilities to learn and represent implicit knowledge by means of adaptive neuro fuzzy inference system (ANFIS).

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