A Probabilistic Rough Set Approach for Water Reservoirs Site Location Decision Making

Shaaban, Shaaban M.; Nabwey, Hossam A.

doi:10.1007/978-3-642-31075-1_27

Cited by 9 publications

(8 citation statements)

References 5 publications

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“…Rough set theory (RST) [5,6] which is one of the successful approximations based mathematical model to deal the imprecision and uncertainty present in knowledge. Many heuristic algorithms are proposed based on rough set theory, also numerous approached based on rough set theory and other theories are investigated to extract decision rules and reduce the dimensionality of dataset [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26].One advantage of the rough set is the creation of readable if-then rules. Such rules have a potential to reveal new patterns in the data material.…”

Section: Introductionmentioning

confidence: 99%

A Method for Fault Prediction of Air Brake System in Vehicles

Nabwey¹

2020

International Journal of Engineering Research and Technology

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Fault diagnosis is a complex problem that concerns effective decision-making. Air brake system is a crucial safety unit and failure of which leads to the loss of vehicle yaw stability and increase in stopping distance of the vehicle. Fault detection and isolation in brake system is critical for continuity of the performance and the safe running of autonomous vehicles. Carrying out timely system diagnosis whenever a fault occur is important to prevent component degradation and vehicle breakdown. This work use the Rough Set Theory to develop fault diagnostic scheme for classifying the "fault" and "Nofault" conditions of air brake system with the knowledge of wheel speed sensor data. The rough set reduction principle is applied to find all reducts, and then a set of generalized classification rules for predicting the faults of Air brake system was extracted. The results show that the presented method can effectively enrich the vehicle condition monitoring system, able to give a feedback to the driver regarding the working condition of air brake system, detect and identify the location of faults, minimize the resources, such as time, cost of maintenance, etc.

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Section: Introductionmentioning

confidence: 99%

A Method for Fault Prediction of Air Brake System in Vehicles

Nabwey¹

2020

International Journal of Engineering Research and Technology

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“…An approach based on Rough Sets Theory and Grey System for Implementation of Rule-Based Control for Sustainability of Rotary Clinker Kiln was introduced in [40]. Shaaban et al [41,42] used rough set methodology for steam turbine-generator fault diagnosis and for water reservoirs site location decision making, respectively. For more applications see [43][44][45][46][47][48][49][50][51][52][53][54].…”

Section: Introductionmentioning

confidence: 99%

Integration of Group Method Analysis and Rough Sets Theory to Investigate Heat and Mass Transfer of the Flow of a Non-Newtonian Nanofluid towards a Vertical Stretching Surface

Nabwey¹

2020

IJIES

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This work reports how to utilize rough set theory and group method analysis for generating a set of rules to investigate heat and mass transfer of mixed convection stagnation point flow of a non-Newtonian nanofluid towards a vertical stretching surface. By utilizing group method analysis, the main partial differential equations which describe the flow are rehabilitated to nonlinear Ordinary Differential Equations (ODEs). Then, the resultant nonlinear ODEs are solved numerically by applying the implicit finite-difference scheme. The numerical values thus obtained are depicted in tabular form and the basic principles of rough sets are applied to get all reducts and finally a group of generalized rules are extracted to predict the value of local Nusselt number and local skin-friction coefficient. The outcomes demonstrate the novelty of the current work which can be summarized as hybridization of group method analysis and rough set theory to use in the field of fluid dynamics effectively. The resultant set of generalized classification rules which performed with basic logic functions can be considered as knowledge base with high accuracy and may be valuable in many engineering applications like power production, thermal extrusion systems and microelectronics.

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“…In the fault classification step, the selected features are used to train artificial intelligence techniques like k-nearest neighbor (kNN), artificial neural networks and support vector machine (SVM), fuzzy sets [8][9][10], rough set theory (RST) [11,12] which is one of the successful approximation based mathematical model to deal the imprecision and uncertainty present in knowledge. Many heuristic algorithms are proposed based on rough set theory, also numerous approached based on rough set theory and other theories are investigated to extract decision rules and reduce the dimensionality of dataset [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30]…”

Section: Introductionmentioning

confidence: 99%

Identification of Short Circuit Fault Location in Voltage Source Inverters Based On Rough Set Theory

Nabwey¹

2020

International Journal of Engineering Research and Technology

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Fault diagnosis is a complex problem that concerns effective decision-making. However, with the increased complexity of equipments and enrichment in data collection methods, the task of fault diagnosis has become increasingly difficult and its complexity almost unmanageable using traditional techniques. In this paper, a Method of the Rules Extraction for Detection and Identification of Short Circuit Fault Location in Voltage Source Inverters Based on Rough Set Theory is presented. The rough set reduction technique is applied to find all reducts. After that the principles of hypergraph was applied to determine the minimal transversal of reducts. Finally, a set of generalized rules for Short Circuit Fault Location was extracted. The extracted rules are performed with basic logic functions so a digital diagnostic circuit can be obtained. The results show that the presented method can effectively detect and identify the location of faults and do not depend on switch parameters, increase the efficiency and accuracy of diagnosis and can avoid the fault diagnosis dimensional disaster problem.

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A Probabilistic Rough Set Approach for Water Reservoirs Site Location Decision Making

Cited by 9 publications

References 5 publications

A Method for Fault Prediction of Air Brake System in Vehicles

A Method for Fault Prediction of Air Brake System in Vehicles

Integration of Group Method Analysis and Rough Sets Theory to Investigate Heat and Mass Transfer of the Flow of a Non-Newtonian Nanofluid towards a Vertical Stretching Surface

Identification of Short Circuit Fault Location in Voltage Source Inverters Based On Rough Set Theory

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