Contribution to Improve Database Classification Algorithms for Multi-Database Mining

Miloudi, Salim,Rahal, Sid Ahmed,Khiat, Salim Korea Information Processing Society 2018 Journal of information processing systems Vol.14 No.3

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact, when a multi-branch company needs to explore its distributed data for decision making, it is imperative to classify these multiple databases into similar clusters before analyzing the data. To search for the best classification of a set of n databases, existing algorithms generate from 1 to ($n^2-n$)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification are subsets of clusters in the next classification), existing algorithms generate each classification independently, that is, without taking into account the use of clusters from the previous classification. Consequently, existing algorithms are time consuming, especially when the number of candidate classifications increases. To overcome the latter problem, we propose in this paper an efficient approach that represents the problem of classifying the multiple databases as a problem of identifying the connected components of an undirected weighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of our algorithm against existing works and that it overcomes the problem of increase in the execution time.

Contribution to Improve Database Classification Algorithms for Multi-Database Mining

Salim Miloudi,Sid Ahmed Rahal,Salim Khiat 한국정보처리학회 2018 Journal of information processing systems Vol.14 No.3

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact,when a multi-branch company needs to explore its distributed data for decision making, it is imperative toclassify these multiple databases into similar clusters before analyzing the data. To search for the bestclassification of a set of n databases, existing algorithms generate from 1 to (n2–n)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification aresubsets of clusters in the next classification), existing algorithms generate each classification independently,that is, without taking into account the use of clusters from the previous classification. Consequently, existingalgorithms are time consuming, especially when the number of candidate classifications increases. Toovercome the latter problem, we propose in this paper an efficient approach that represents the problem ofclassifying the multiple databases as a problem of identifying the connected components of an undirectedweighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of ouralgorithm against existing works and that it overcomes the problem of increase in the execution time.

Improved Direct Torque Control of Permanent Magnet Synchronous Electrical Vehicle Motor with Proportional-Integral Resistance Estimator

Hartani, Kada,Miloud, Yahia,Miloudi, Abdellah The Korean Institute of Electrical Engineers 2010 Journal of Electrical Engineering & Technology Vol.5 No.3

Electric vehicles (EVs) require fast torque response and high drive efficiency. This paper describes a control scheme of fuzzy direct torque control of permanent magnet synchronous motor for EVs. This control strategy is extensively used in EV application. With direct torque control (DTC), the electromagnetic torque and stator flux can be estimated using the measured stator voltages and currents. The estimation depends on motor parameters, except for the stator resistance. The variation of stator resistance due to changes in temperature or frequency downgrades the performance of DTC, which is controlled by introducing errors in the estimated flux linkage vector and the electromagnetic torque. Thus, compensation for the effect of stator resistance variation becomes necessary. This work proposes the estimation of the stator resistance and its compensation using a proportional-integral estimation method. An electronic differential has been also used, which has the advantage of replacing loose, heavy, and inefficient mechanical transmission and mechanical differential with a more efficient, light, and small electric motors that are directly coupled to the wheels through a single gear or an in-wheel motor.

Safety Levels Apportionment in Railway System

Meriem Rafrafi,EI Miloudi EI Koursi,Thomas Bourdeaud"HuY 한국철도학회 2008 International Journal of Railway Vol.1 No.4

The creation of a single European rail transport market it is important to increase confidence between the actors on the market and between member states who shall ensure that railway safety is generally maintained and, where reasonably practicable, continuously improved. For this purpose the European railway safety directive introduces a mechanism to adopt a Common Safety Targets (CST) expressed in risk acceptance criteria for individuals and for society. This paper focuses on the apportionment of safety targets for European railway system. We develop a generic approach based on the Functional Hazard Analysis (FHA), to analyse the safety of railway systems for a unified European network and to com￢ply with the CSTs required by the European railway Safety Directive. We suggest to combine the FHA technique with the functional railway architecture to allocate the safety targets to the railway functions.

Improved Direct Torque Control of Permanent Magnet Synchronous Electrical Vehicle Motor with Proportional-Integral Resistance Estimator

Kada Hartani,Yahia Miloud,Abdellah Miloudi 대한전기학회 2010 Journal of Electrical Engineering & Technology Vol.5 No.3

Electric vehicles (EVs) require fast torque response and high drive efficiency. This paper describes a control scheme of fuzzy direct torque control of permanent magnet synchronous motor for EVs. This control strategy is extensively used in EV application. With direct torque control (DTC), the electromagnetic torque and stator flux can be estimated using the measured stator voltages and currents. The estimation depends on motor parameters, except for the stator resistance. The variation of stator resistance due to changes in temperature or frequency downgrades the performance of DTC, which is controlled by introducing errors in the estimated flux linkage vector and the electromagnetic torque. Thus, compensation for the effect of stator resistance variation becomes necessary. This work proposes the estimation of the stator resistance and its compensation using a proportional-integral estimation method. An electronic differential has been also used, which has the advantage of replacing loose, heavy, and inefficient mechanical transmission and mechanical differential with a more efficient, light, and small electric motors that are directly coupled to the wheels through a single gear or an in-wheel motor.

Safety Levels Apportionment in Railway System

Rafrafi, Meriem,El Koursi, El Miloudi,Bourdeaud'Huy, Thomas The Korean Society for Railway 2008 International Journal of Railway Vol.1 No.4

The creation of a single European rail transport market it is important to increase confidence between the actors on the market and between member states who shall ensure that railway safety is generally maintained and, where reasonably practicable, continuously improved. For this purpose the European railway safety directive introduces a mechanism to adopt a Common Safety Targets (CST) expressed in risk acceptance criteria for individuals and for society. This paper focuses on the apportionment of safety targets for European railway system. We develop a generic approach based on the Functional Hazard Analysis (FHA), to analyse the safety of railway systems for a unified European network and to comply with the CSTs required by the European railway Safety Directive. We suggest to combine the FHA technique with the functional railway architecture to allocate the safety targets to the railway functions.