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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Rengaraj Hema
Madha Engineering College

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Deep neural network with fuzzy algorithm to improve power and traffic-aware reliable reactive routing Radhakrishnan Murugesan; Satish Kanapala; Subash Rajendran; Prathaban Banu Priya; Rathinasabapathy Ramadevi; Natarajan Duraichi; Rengaraj Hema
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp380-388

Abstract

In wireless networks, link breaks, and restricted resources create fundamental challenges for maintaining network applications. Several wireless network routing techniques concentrate on power efficiency to expand the network lifetime, but the traffic and reliability parameters are not the primary concern. Though, these techniques are not capable of dealing with the wireless network. Hence, this paper proposes deep neural network (DNN) with a fuzzy algorithm to improve power and traffic-aware reliable reactive routing (PTAR) in wireless networks. The wireless network is formed by clustering by the node power and selects the cluster head (CH) based on a fuzzy algorithm. The wireless node power level, node buffer space, and node reliability to consider the input parameters of the fuzzy system. Then thefuzzy algorithm gives the output for CH round length. This selected CH improves the node reliability, power efficiency with minimized network congestion. Then we use a DNN algorithm to choose an optimal relay by applying an adaptive load balance factor in the network. DNN is a machine learning algorithm, and it provides high accuracy. From the simulation results, the PTAR approach improves the network performance, such as packet received ratio, delay, residual energy, and routing overhead.
Performance improvement in photovoltaic-grid system using genetic algorithm Rangasamy Sankar; Durairaj Chandrakala; Rengaraj Hema; Dakshnamurthy Padmapriya
Indonesian Journal of Electrical Engineering and Computer Science Vol 32, No 3: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v32.i3.pp1327-1336

Abstract

In recent, photov oltaic (PV) power generation has increased in importance. The growing significance of PV power production has generated the demand for enhancing energy efficiency via continuous operation at the maximum power point (MPP). To enable effective MPP trac king, the suggested system integrates a proportional - integral (PI) controller with the p erturb and observe (P&O) technique. In order to improve performance in a PV grid system, this work provides a unique method using a proportional - integral - derivative (PI D) controller optimized using a genetic algorithm (GA). The proposed controller architecture integrates the GA algorithm with a PID controller in the voltage source inverter (VSI) of the PV system. To enable effective grid integration, the GA is used to co ntinually optimize the PID controller settings. The converter’ s design criteria and computations are discussed, and MATLAB simulations are used to assess the system’ s performance. Compared to traditional PID controllers, the observed findings show increas ed efficiency, cheaper cost, and enhanced controllability. The suggested GA - PID controller offers opportunities for more study and development in this area while showing potential for improving PV grid system performance.
Co-Authors Dakshnamurthy Padmapriya Durairaj Chandrakala Natarajan Duraichi Prathaban Banu Priya Radhakrishnan Murugesan Rangasamy Sankar Rathinasabapathy Ramadevi Satish Kanapala Subash Rajendran