Parallel propagation in the description-logic system FLEX

1997 ◽  
pp. 181-207
Author(s):  
Frank W. Bergmann ◽  
J. Joachim Quantz
Keyword(s):  
Description Logic ◽  
Parallel Propagation ◽  
Logic System

Hierarchy Organization Model Based on the Logic of Tasks

2013 ◽  
Vol 310 ◽  
pp. 644-649
Author(s):  
Cen Yu ◽  
Wei Jia Zhou
Keyword(s):  
System Application ◽  
Description Logic ◽  
Robot System ◽  
Collaborative Robots ◽  
Organization Model ◽  
Model Based ◽  
Task Oriented ◽  
Logic System ◽  
Multi Robot

Hierarchy organization is suitable for multi-robot system application. Robot or collaborative robots group is considered as an agent, then the organization model consists of agents and the relations between them. This paper introduces the logic of tasks combined with description logic to construct logic system. According to related works [4], we can prove is decidable, complete and sound. Based on the logic system, author presented a formal task-oriented hierarchy organization model that can deduce a plan with a strategy can complete task or not.

ONTOLOGY-BASED SEMANTIC VERIFICATION FOR UML BEHAVIORAL MODELS

2013 ◽  
Vol 23 (02) ◽  
pp. 117-145 ◽  
Author(s):  
HONGYUE HE ◽  
ZHIXUE WANG ◽  
QINGCHAO DONG ◽  
WEIZHONG ZHANG ◽  
WEIXING ZHU
Keyword(s):  
Description Logic ◽  
System Analysis ◽  
Formal Semantics ◽  
Behavioral Model ◽  
Model Verification ◽  
Behavioral Models ◽  
Analysis And Design ◽  
Requirements Modeling ◽  
Logic System

UML is now popularly applied as a requirements modeling language for software system analysis and design, and the dynamic behaviors of system are described in UML behavioral model. As the UML model suffers from lack of well-defined formal semantics, it is difficult to formally analyze and verify the behavioral model. The paper presents a method of UML behavioral model verification based on Description Logic system and its formal inference. The semantics of UML behavioral models is divided into static semantics and dynamic semantics, which are formally specified in OWL DL ontology and DL-Safe rules. To check the consistency of the behavioral models, the algorithms are provided for transforming UML behavioral models into OWL DL ontology, and hence model consistency can be verified through formal reasoning with a DL supporting reasoner Pellet. A case study is provided to demonstrate applicability of the method.

Application Fuzzy Logic System for Accurate Sheet Trim Shower Position

2019 ◽  
Vol 3 (1) ◽  
pp. 186-192
Author(s):  
Yudi Wibawa
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Automation System ◽  
Paper Making ◽  
System A ◽  
Accurate Position ◽  
And Performance ◽  
Better Than ◽  
Logic System

This paper aims to study for accurate sheet trim shower position for paper making process. An accurate position is required in an automation system. A mathematical model of DC motor is used to obtain a transfer function between shaft position and applied voltage. PID controller with Ziegler-Nichols and Hang-tuning rule and Fuzzy logic controller for controlling position accuracy are required. The result reference explains it that the FLC is better than other methods and performance characteristics also improve the control of DC motor.

A New Hardware Architecture for Fuzzy Logic System Acceleration

2016 ◽  
Vol 12 (2) ◽  
pp. 188-197
Author(s):  
A yahoo.com ◽  
Aumalhuda Gani Abood aumalhuda ◽  
A comp ◽  
Dr. Mohammed A. Jodha ◽  
Dr. Majid A. Alwan
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Hardware Architecture ◽  
Logic System

Penerapan Logika Samar dalam Peramalan Data Runtun Waktu

2011 ◽  
Vol 3 (2) ◽  
pp. 11-15
Author(s):  
Seng Hansun
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Time Series Analysis ◽  
Fuzzy Sets ◽  
Fuzzy System ◽  
Time Series Data ◽  
Fuzzy Logic System ◽  
Series Data ◽  
Series Analysis ◽  
Logic System

Recently, there are so many soft computing methods been used in time series analysis. One of these methods is fuzzy logic system. In this paper, we will try to implement fuzzy logic system to predict a non-stationary time series data. The data we use here is Mackey-Glass chaotic time series. We also use MATLAB software to predict the time series data, which have been divided into four groups of input-output pairs. These groups then will be used as the input variables of the fuzzy logic system. There are two scenarios been used in this paper, first is by using seven fuzzy sets, and second is by using fifteen fuzzy sets. The result shows that the fuzzy system with fifteen fuzzy sets give a better forecasting result than the fuzzy system with seven fuzzy sets. Index Terms—forecasting, fuzzy logic, Mackey-Glass chaotic, MATLAB, time series analysis

Deciding Query Entailment for Fuzzy Description Logic Knowledge Bases：The f-SH Family

2012 ◽  
Vol 35 (4) ◽  
pp. 767-785
Author(s):  
Jing-Wei CHENG ◽  
Zong-Min MA ◽  
Li YAN ◽  
Fu ZHANG
Keyword(s):  
Description Logic ◽  
Fuzzy Description

Semantics of OWL-S process model based on temporal description logic

2013 ◽  
Vol 33 (1) ◽  
pp. 266-269 ◽  
Author(s):  
Ming LI ◽  
Shiyi LIU ◽  
Fuzhong NIAN
Keyword(s):  
Process Model ◽  
Description Logic ◽  
Model Based

IMPROVING EIGENSPACE-BASED FUZZY LOGIC SYSTEM USING A LINEAR INTERPOLATION SCHEME FOR SPEECH PATTERN RECOGNITION

2013 ◽  
Vol 37 (3) ◽  
pp. 611-620
Author(s):  
Ing-Jr Ding ◽  
Chih-Ta Yen
Keyword(s):  
Pattern Recognition ◽  
Fuzzy Logic ◽  
Recognition Performance ◽  
Linear Interpolation ◽  
Fuzzy Logic System ◽  
Interpolation Scheme ◽  
Speech Pattern ◽  
Eigen Value ◽  
Target Speaker ◽  
Logic System

The Eigen-FLS approach using an eigenspace-based scheme for fast fuzzy logic system (FLS) establishments has been attempted successfully in speech pattern recognition. However, speech pattern recognition by Eigen-FLS will still encounter a dissatisfactory recognition performance when the collected data for eigen value calculations of the FLS eigenspace is scarce. To tackle this issue, this paper proposes two improved-versioned Eigen-FLS methods, incremental MLED Eigen-FLS and EigenMLLR-like Eigen-FLS, both of which use a linear interpolation scheme for properly adjusting the target speaker’s Eigen-FLS model derived from an FLS eigenspace. Developed incremental MLED Eigen-FLS and EigenMLLR-like Eigen-FLS are superior to conventional Eigen-FLS especially in the situation of insufficient data from the target speaker.

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