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bsj-8414
LINE REGULAR FUZZY SEMIGRAPHS
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           This paper introduce two types of edge degrees (line degree and near line degree) and total edge degrees (total line degree and total near line degree) of an edge in a fuzzy semigraph, where a fuzzy semigraph is defined as (V, σ, μ, η) defined on a semigraph G* in which σ : V → [0, 1], μ : VxV → [0, 1] and η : X → [0, 1] satisfy the conditions that for all the vertices u, v in the vertex set,  μ(u, v) ≤ σ(u) ᴧ σ(v) and  η(e) = μ(u1, u2) ᴧ μ(u2, u3) ᴧ … ᴧ μ(un-1, un) ≤ σ(u1) ᴧ σ(un), if e = (u1, u2, …, un), n ≥ 2 is an edge in the semigraph G*, in which a semigraph is defined as a pair of sets (V, X) in which the vertex set V is a non - empty set and edge set X is a set of n – tuples for various n ≥ 2, of distinct elements of V with the properties that, any two elements in the edge set X has at most one vertex in common and for any two edges (ɑ1, ɑ2,…, ɑn ) and (b1, b2,…, bm)  in the edge set X are equal if, and only if, n = m and either one of the conditions ɑj = bj  or ɑj = bn-j+1 occur for j where the value of j lies between 1 and n. In addition to that edge regularities (line regular and near line regular) and total edge regularities (total line regular and total near line regular) of the corresponding edge degrees and total edge degrees are studied, their properties are examined and a few results connecting vertex regularity and edge regularity of a fuzzy semigraph are obtained.

2020 Mathematics Subject Classification: 05C72, 05C07.

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Publication Date
Sun Jan 01 2017
Journal Name
International Journal Of Mathematics In Operational Research
A single server fuzzy queues with priority and unequal service rates
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Publication Date
Sat Nov 07 2020
Journal Name
Theory And Practice Of Mathematics And Computer Science
Discussion on Bipolar Fuzzy n-fold KU-ideal of KU-algebras
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Publication Date
Sun Jan 01 2006
Journal Name
Journal Of Engineering
SELF ORGANIZING FUZZY CONTROLLER FOR A NON-LINEAR TIME VARYING SYSTEM
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This paper proposes a self organizing fuzzy controller as an enhancement level of the fuzzy controller. The adjustment mechanism provides explicit adaptation to tune and update the position of the output membership functions of the fuzzy controller. Simulation results show that this controller is capable of controlling a non-linear time varying system so that the performance of the system improves so as to reach the desired state in a less number of samples.

Publication Date
Tue Jan 01 2008
Journal Name
Journal Of Engineering
USING FUZZY LOGIC CONTROLLER FOR A TWO- TANK LEVEL CONTROL SYSTEM
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This paper presents a fuzzy logic controller for a two-tank level control system, which is a process with a dead time. The fuzzy controller is a proportional-integral (PI-like) fuzzy controller which is suitable for steady state behavior of the system. Transient behavior of the system was improved without the need for a derivative action by suitable change in the rule base of the controller. Simulation results showed the step response of the two-tank level control system when this controller was used to control this plant and the effect of the dead time on the response of the system.

Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Parametric Nonlinear Programming Approach with Fuzzy Queues Using Hexagonal Membership Functions
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Publication Date
Wed Apr 01 2015
Journal Name
2015 Annual Ieee Systems Conference (syscon) Proceedings
Automatic generation of fuzzy classification rules using granulation-based adaptive clustering
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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials & Continua
Takagi–Sugeno Fuzzy Modeling and Control for Effective Robotic Manipulator Motion
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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Design of Hybrid Neural Fuzzy Controller for Human Robotic Leg System
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 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Generalizations of Fuzzy k-ideals in a KU-algebra with Semigroup
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Abstract<p>We present the notion of bipolar fuzzy k-ideals with thresholds (<italic>θ, λ</italic>) of a KU-algebra with semigroup and give some basic properties of this ideal. Also, we study some relations about a bipolar fuzzy k-ideal with thresholds (<italic>θ, λ</italic>) and a k-ideal of a KU-semigroup.</p>
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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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