A comparison of discrete and hybrid models of an aircraft conflict detection algorithm

Identification of conflicting questions in the PARES system

The International Review of Research in Open and Distributed Learning ◽

10.19173/irrodl.v13i3.1176 ◽

2012 ◽

Vol 13 (3) ◽

pp. 297 ◽

Cited By ~ 2

Author(s):

Avgoustos Tsinakos ◽

Ioannis Kazanidis

Keyword(s):

Continuing Education ◽

Statistical Evaluation ◽

Academic Staff ◽

Vector Space Model ◽

Detection Algorithm ◽

Conflict Detection ◽

Knowledge Assessment ◽

Space Model ◽

Practice Tests ◽

Test Suites

Student testing and knowledge assessment is a significant aspect of the learning process. In a number of cases, it is expedient not to present the exact same test to all learners all the time (Pritchett, 1999). This may be desired so that cheating in the exam is made harder to carry out or so that the learners can take several practice tests on the same subject as part of the course. This study presents an e-testing platform, namely PARES, which aims to provide assessment services to academic staff by facilitating the creation and management of question banks and powering the delivery of nondeterministically generated test suites. PARES uses a conflict detection algorithm based on the vector space model to compute the similarity between questions and exclude questions which are deemed to have an unacceptably large similarity from appearing in the same test suite. The conflict detection algorithm and a statistical evaluation of its accuracy are presented. Evaluation results show that PARES succeeds in detecting question types at about 90% and its efficiency can be further increased through continuing education and enrichment of the system’s correlation vocabulary.

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Aircraft Conflict Risk Assessment Based on Particle Filter

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.602-605.3416 ◽

2014 ◽

Vol 602-605 ◽

pp. 3416-3420

Author(s):

Wen Peng Zhai ◽

Hao Wu ◽

Lan Ma

Keyword(s):

Particle Filter ◽

Early Stage ◽

Random Perturbation ◽

Kinematic Model ◽

Detection Algorithm ◽

Conflict Detection ◽

Collision Risk ◽

Free Flight ◽

Risk Probability ◽

Particle Filter Algorithm

Free flight is a method to resolve airspace congestion problem, but raise safety problem. In this paper, with the influence of wind and the presence of positioning error, the model of conflict detection based on particle filter algorithm is presented. According to the flight kinematic model with the influence of random factors, the target trajectory is generated. The particle filter algorithm is used for estimating the real flight trajectory. The flight collision risk probability is calculated. By simulation calculation, the conflict detection with particle filter algorism improves the accuracy of collision risk probability estimation. The results show that the particle filter conflict detection algorithm reduces the estimation and conflict detection error caused by random perturbation. The method can be applied to identify conflict in the early stage in the study of flight free flight.

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A three dimensional scalable and distributed conflict detection algorithm for unmanned aerial vehicles

2016 IEEE Wireless Communications and Networking Conference ◽

10.1109/wcnc.2016.7565072 ◽

2016 ◽

Cited By ~ 1

Author(s):

Imen Mahjri ◽

Amine Dhraief ◽

Abdelfettah Belghith

Keyword(s):

Unmanned Aerial Vehicles ◽

Three Dimensional ◽

Detection Algorithm ◽

Conflict Detection ◽

Aerial Vehicles

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BFX: DIAGNOSING CONFLICTING REQUIREMENTS IN CONSTRAINT-BASED RECOMMENDATION

International Journal of Artificial Intelligence Tools ◽

10.1142/s0218213011000164 ◽

2011 ◽

Vol 20 (02) ◽

pp. 297-312 ◽

Cited By ~ 2

Author(s):

MONIKA SCHUBERT ◽

ALEXANDER FELFERNIG

Keyword(s):

Performance Evaluation ◽

Structural Properties ◽

Detection Algorithm ◽

Conflict Detection ◽

Comparative Performance ◽

Detection Algorithms ◽

Minimal Sets ◽

The Given

When interacting with constraint-based recommender applications, users describe their preferences with the goal of identifying the products that fit their wishes and needs. In such a scenario, users are repeatedly adapting and changing their requirements. As a consequence, situations occur where none of the products completely fulfils the given set of requirements and users need a support in terms of an indicator of minimal sets of requirements that need to be changed in order to be able to find a recommendation. The identification of such minimal sets relies heavily on the existence of (minimal) conflict sets. In this paper we introduce BFX (Boosted FastXplain), a conflict detection algorithm which exploits the basic structural properties of constraint-based recommendation problems. BFX shows a significantly better performance compared to existing conflict detection algorithms. In order to demonstrate the performance of BFX, we report the results of a comparative performance evaluation.

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