On the Use of Linear Combination in PWCP-Nets

2018 ◽  
Vol 26 (01) ◽  
pp. 1-26
Author(s):  
Sleh El Fidha ◽  
Nahla Ben Amor
Keyword(s):  
Probability Distribution ◽  
Linear Combination ◽  
Model Uncertainty ◽  
Experimental Results ◽  
Relative Importance ◽  
New Approach ◽  
New Model ◽  
Conditional Preference ◽  
Conditional Preference Networks ◽  
Qualitative Preferences

Conditional preference networks (CP-nets) are a compact but powerful formalism to represent and reason with qualitative preferences using the notion of conditional preferential independence. However, they suffer from incomparabilities between possible outcomes. Several works have attempted to overcome this weakness by quantifying CP-nets. This paper proposes a new approach combining two of the most interesting extensions of CP-nets, namely Probabilistic CP-nets (PCP-nets) using probability distribution to model uncertainty in different preference statements and Weighted CP-nets (WCP-nets) adding weights to express the relative importance of some attribute values regarding others. The new model so-called PWCP-nets combines the two models by handling both uncertainty and weights. Experimental results show the efficiency of this rich extension of CP-nets compared to PCP-nets and WCP-nets.

scholarly journals Rank Pruning for Dominance Queries in CP-Nets

2019 ◽  
Vol 64 ◽  
pp. 55-107
Author(s):  
Kathryn Laing ◽  
Peter Adam Thwaites ◽  
John Paul Gosling
Keyword(s):  
Graphical Representation ◽  
User Preferences ◽  
Experimental Results ◽  
Dominance Testing ◽  
Conditional Preference ◽  
Novel Method ◽  
Conditional Preferences ◽  
Conditional Preference Networks ◽  
Testing Efficiency

Conditional preference networks (CP-nets) are a graphical representation of a person’s (conditional) preferences over a set of discrete features. In this paper, we introduce a novel method of quantifying preference for any given outcome based on a CP-net representation of a user’s preferences. We demonstrate that these values are useful for reasoning about user preferences. In particular, they allow us to order (any subset of) the possible outcomes in accordance with the user’s preferences. Further, these values can be used to improve the efficiency of outcome dominance testing. That is, given a pair of outcomes, we can determine which the user prefers more efficiently. Through experimental results, we show that this method is more effective than existing techniques for improving dominance testing efficiency. We show that the above results also hold for CP-nets that express indifference between variable values.

scholarly journals Sequential Learning-based IaaS Composition

2021 ◽  
Vol 15 (3) ◽  
pp. 1-37
Author(s):  
Sajib Mistry ◽  
Sheik Mohammad Mostakim Fattah ◽  
Athman Bouguettaya
Keyword(s):  
Three Dimensional ◽  
Sequential Optimization ◽  
Preference Ranking ◽  
Learning Approach ◽  
Agglomerative Clustering ◽  
Sequential Selection ◽  
Conditional Preference ◽  
Conditional Preference Networks ◽  
Qualitative Preferences

We propose a novel Infrastructure-as-a-Service composition framework that selects an optimal set of consumer requests according to the provider’s qualitative preferences on long-term service provisions. Decision variables are included in the temporal conditional preference networks to represent qualitative preferences for both short-term and long-term consumers. The global preference ranking of a set of requests is computed using a k -d tree indexing-based temporal similarity measure approach. We propose an extended three-dimensional Q-learning approach to maximize the global preference ranking. We design the on-policy-based sequential selection learning approach that applies the length of request to accept or reject requests in a composition. The proposed on-policy-based learning method reuses historical experiences or policies of sequential optimization using an agglomerative clustering approach. Experimental results prove the feasibility of the proposed framework.

Yaw Galloping of a TLWP Platform Under High Speed Currents by Analytical Methods and its Comparison With Experimental Results

2017 ◽  
Author(s):  
Francisco Lamas ◽  
Miguel A. M. Ramirez ◽  
Antonio Carlos Fernandes
Keyword(s):  
High Speed ◽  
Production Systems ◽  
Experimental Tests ◽  
Experimental Results ◽  
Analytical Methodology ◽  
New Approach ◽  
Laboratory Facilities ◽  
Polynomial Curve ◽  
Computational Fluid Dynamics Cfd ◽  
Cfd Analyses

Flow Induced Motions are always an important subject during both design and operational phases of an offshore platform life. These motions could significantly affect the performance of the platform, including its mooring and oil production systems. These kind of analyses are performed using basically two different approaches: experimental tests with reduced models and, more recently, with Computational Fluid Dynamics (CFD) dynamic analysis. The main objective of this work is to present a new approach, based on an analytical methodology using static CFD analyses to estimate the response on yaw motions of a Tension Leg Wellhead Platform on one of the several types of motions that can be classified as flow-induced motions, known as galloping. The first step is to review the equations that govern the yaw motions of an ocean platform when subjected to currents from different angles of attack. The yaw moment coefficients will be obtained using CFD steady-state analysis, on which the yaw moments will be calculated for several angles of attack, placed around the central angle where the analysis is being carried out. Having the force coefficients plotted against the angle values, we can adjust a polynomial curve around each analysis point in order to evaluate the amplitude of the yaw motion using a limit cycle approach. Other properties of the system which are flow-dependent, such as damping and added mass, will also be estimated using CFD. The last part of this work consists in comparing the analytical results with experimental results obtained at the LOC/COPPE-UFRJ laboratory facilities.

RESTRICTED SOLID-ON-SOLID MODEL: FROM LOCAL MORPHOLOGY TO CORRELATION FUNCTIONS AND SCALING EXPONENTS

2004 ◽  
Vol 18 (06) ◽  
pp. 827-840
Author(s):  
CHIH-CHUN CHIEN ◽  
NING-NING PANG ◽  
WEN-JER TZENG
Keyword(s):  
Computer Simulation ◽  
Probability Distribution ◽  
Correlation Functions ◽  
Master Equations ◽  
Interfacial Phenomena ◽  
Solid Model ◽  
Direct Simulation ◽  
Kpz Equation ◽  
Scaling Exponents ◽  
New Approach

We study the restricted solid-on-solid (RSOS) model by grouping consecutive sites into local configurations and obtain the master equations of the probability distribution of these local configurations in closed forms. The obtained solutions to these equations fit very well with those from direct computer simulation of the RSOS model. To demonstrate the effectiveness of this new approach for studying interfacial phenomena, we then calculate the correlation functions and even scaling exponents based on this obtained probability distribution of local configurations. The results are also consistent very well with those obtained from the KPZ equation or direct simulation of the RSOS model.

A modified Runge-Kutta method

SIMULATION ◽  
1968 ◽  
Vol 10 (5) ◽  
pp. 221-223 ◽  
Author(s):  
A.S. Chai
Keyword(s):  
Error Estimate ◽  
Linear Combination ◽  
Experimental Results ◽  
The Other ◽  
New Method ◽  
Kutta Method ◽  
Starting Values ◽  
Runge Kutta Method ◽  
Runge Kutta ◽  
A Minor

It is possible to replace k2 in a 4th-order Runge-Kutta for mula (also Nth-order 3 ≤ N ≤ 5) by a linear combination of k1 and the ki's in the last step, using the same procedure for computing the other ki's and y as in the standard R-K method. The advantages of the new method are: It re quires one less derivative evaluation, provides an error estimate at each step, gives more accurate results, and needs a minor change to switch to the RK to obtain the starting values. Experimental results are shown in verification of the for mula.

Prediction of soot formation rates: a new approach

1974 ◽  
Vol 338 (1614) ◽  
pp. 375-396 ◽  
Keyword(s):  
Soot Formation ◽  
Rocket Engine ◽  
Experimental Results ◽  
Intermediate Species ◽  
New Approach ◽  
Fundamental Model ◽  
Gas Reactions ◽  
Gaseous Hydrocarbons ◽  
Controlling Processes ◽  
Exhaust Jet

Five processes controlling the production of soot from gaseous hydrocarbons are distinguished: gas reactions producing radical fragments on which nucleation may begin; nucleation; coagulation; growth; and oxidation. A fundamental model capable of taking into account all these processes is described. The model is applied to the conditions of a practical rocket engine, in which production of soot in the exhaust jet is governed by the rate of pyrolysis of methane in the chamber. Predictions made for these conditions agree with experimental results. The rate controlling processes and key intermediate species are identified.

A New Approach for Autonomous Robot Obstacle Avoidance Using PSD Infrared Sensor Combined with Digital Compass

2014 ◽  
Vol 511-512 ◽  
pp. 101-104 ◽  
Author(s):  
Yang Xue ◽  
Jun Tao Yang ◽  
Ya Ling Dong ◽  
Jia Li Shen ◽  
Ru Peng ◽  
...  
Keyword(s):  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Autonomous Robot ◽  
Experimental Results ◽  
Position Sensitive Detector ◽  
Infrared Sensor ◽  
Sensitive Detector ◽  
New Approach ◽  
Position Sensitive

This paper presents a new approach for obstacle avoidance of small mobile robots, which combine the position sensitive detector (PSD) with digital compass. It is important for an autonomous robot to explore its surroundings in performing the task of localization and navigation for searching. Because of the complexity of the environment, one simple kind of sensors is not sufficient for robot to accomplish these tasks. In this paper, the small mobile robots are enabled to identify barriers and distinguish surroundings by using the angle signal from the digital compass which is generally mounted on the robot. Experimental results indicate that this approach based on digital compass shows great potential in autonomous robot obstacle avoidance.

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