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All Journal IAES International Journal of Robotics and Automation (IJRA) Indonesian Journal of Electrical Engineering and Computer Science
Baseem Khan
Hawassa University
Automotive Engineering Electrical & Electronics Engineering

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Application of Unified Power Flow Controller to Improve Steady State Voltage Limit Samina. E. Mubeen; Baseem Khan; R. K. Nema
IAES International Journal of Robotics and Automation (IJRA) Vol 6, No 4: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (541.375 KB) | DOI: 10.11591/ijra.v6i4.pp277-285

Abstract

This paper utilizes the voltage source model of Unified Power Flow Controller (UPFC) and examines its abilities in mitigating the steady state stability margins of electric power system. It analyzes its behavior for different controls strategies and proposes the most efficient mode of controlling the controller for voltage stability enhancement. A systematic analytical methodology based on the concept of modal analysis of the modified load flow equations is employed to identify the area in a power system which is most prone voltage instability. Also to identify the most effective point of placement for the UPFC, a computer program has been developed using MATLAB. The results of analysis on 14 bus system is presented here as a case study.
An intelligent time aware food recommender system using support vector machine Minakshi Panwar; Ashish Sharma; Om Prakash Mahela; Baseem Khan; Ahmed Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp620-629

Abstract

This paper formulated a support vector machine powered time-aware food recommender system (SVMTAFRS) to recommend healthy food for the customers. The rated food item incorporates the user preference (UP) in terms of calories, nutrition factor, and all food contents required for a healthy diet. This also takes into account the user age, time of day and week day while predicting the food rating. The SVMTAFRS involves two steps for computation of user identity document (UID) and predicted food rating (PFR). UID is computed considering the customer age (CA), UP in terms of calories and suitable weight factors. PFR is computed considering the UID and time of day (TOD). PFR for week end day is computed by multiplying the PFR by week end multiplying factor (WEMF). Support vector machine (SVM) is used for recommending the suitable healthy food for customer in terms of correct values of PFR. Efficacy of PFR is tested in terms of mean absolute error (MAE) and root mean squared error (RMSE). This is established that performance of the SVMTAFRS is superior compared to the rule-based food recommender system (RBFRS).
Co-Authors Ahmed Ali Ashish Sharma Minakshi Panwar Om Prakash Mahela R. K. Nema Samina. E. Mubeen