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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6,301 Documents
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Tunicate swarm algorithm based maximum power point tracking for photovoltaic system under non-uniform irradiation Evi Nafiatus Sholikhah; Novie Ayub Windarko; Bambang Sumantri
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4559-4570

Abstract

A new maximum power point tracking (MPPT) technique based on the bio-inspired metaheuristic algorithm for photovoltaic system (PV system) is proposed, namely tunicate swarm algorithm-based MPPT (TSA-MPPT). The proposed algorithm is implemented on the PV system with five PV modules arranged in series and integrated with DC-DC buck converter. Then, the PV system is tested in a simulation using PowerSim (PSIM) software. TSA-MPPT is tested under varying irradiation conditions both uniform irradiation and non-uniform irradiation. Furthermore, to evaluate the performance, TSA-MPPT is compared with perturb & observe-based MPPT (P&O-MPPT) and particle swarm optimization-based MPPT (PSO-MPPT). The TSA-MPPT has an accuracy of 99% and has a reasonably practical capability compared to the MPPT technique, which already existed before.
Optimal population size of particle swarm optimization for photovoltaic systems under partial shading condition Norazlan Hashim; Nik Fasdi Nik Ismail; Dalina Johari; Ismail Musirin; Azhan Ab. Rahman
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4599-4613

Abstract

Particle swarm optimization (PSO) is the most widely used soft computing algorithm in photovoltaic systems to address partial shading conditions (PSC). The success of the PSO run heavily depends on the initial population size (NP). A higher NP increases the probability of a global peak (GP) solution, but at the expense of a longer convergence time. To find the optimal value of NP, a trade-off is typically made between a high success rate and a reasonable convergence time. The most used trade-off method is a trial-and-error approach that lacks explicit guidelines and empirical evidence from detailed analysis, which can affect data reproducibility when different systems are used. Hence, this study proposes an empirical trade-off method based on the performance index (PI) indicator, which takes into account the weighted importance of success rate and convergence time. Furthermore, the impact of NP on achieving a successful PSO was empirically investigated, with the PSO tested with 16 different NPs ranging from 3 to 50, and 10,000 independent runs on various PSC problems. Overall, this study found that the best NP to use was 25, which had the best average PI value of 0.9373 for solving all PSC problems under consideration.
Quantum dot phosphors CaS:Ce3+ and CaS:Pb2+, Mn2+ for improvements of white light-emitting diodes optic characteristics Dieu An Nguyen Thi; My Hanh Nguyen Thi; Phuc Dang Huu
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4782-4789

Abstract

The goal of this study is to discover a new method that uses standard phosphors and quantum dots to improve the lighting qualities and heat manipulation of white light-emitting diodes (WLEDs). Despite the popularity as a good ingredient that offers good color rendering properties, quantum dots (QDs) have not been widely employed in the fabrication of WLEDs, particularly, the utilization of QDs-phosphor-mixed nanocomposite is limited. We propose a unique packaging design based on the research’s experimental findings. The layer of nanocomposites consisting of QDs and phosphors is horizontally positioned to the WLED for optimal lighting and heating efficiency. This study simulated and used four distinguishing white LEDs forms: mono-layer phosphorus, two double-layer remote phosphors featuring yellowish-red and yellowish-green organizations, and a triple-layer phosphor. In terms of color rendering and luminous outputs, the triple-layer phosphor configuration outperforms the other implementations, as per the finding.
Photovoltaic parameters estimation of poly-crystalline and mono-crystalline modules using an improved population dynamic differential evolution algorithm Ayong Hiendro; Ismail Yusuf; Fitriah Husin; Kho Hie Khwee
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4538-4548

Abstract

Photovoltaic (PV) parameters estimation from the experimental current and voltage data of PV modules is vital for monitoring and evaluating the performance of PV power generation systems. Moreover, the PV parameters can be used to predict current-voltage (I-V) behavior to control the power output of the PV modules. This paper aimed to propose an improved differential evolution (DE) integrated with a dynamic population sizing strategy to estimate the PV module model parameters accurately. This study used two popular PV module technologies, i.e., poly-crystalline and mono-crystalline. The optimized PV parameters were validated with the measured data and compared with other recent meta-heuristic algorithms. The proposed population dynamic differential evolution (PDDE) algorithm demonstrated high accuracy in estimating PV parameters and provided perfect approximations of the measured I-V and power-voltage (P-V) data from real PV modules. The PDDE obtained the best and the mean RMSE value of 2.4251E-03 on the poly-crystalline Photowatt-PWP201, while the best and the mean RMSE value on the mono-crystalline STM6-40/36 was 1.7298E-03. The PDDE algorithm showed outstanding accuracy performance and was competitive with the conventional DE and the existing algorithms in the literature.
Sensor evaluation for hand grip strength Soly Mathew Biju; Hashir Zahid Sheikh
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4756-4764

Abstract

This paper discusses the evaluation of the sensors used in the hand grip strength glove. The glove comprises of flex and force resisting sensors. Force resisting sensor determines the force applied by various parts of the palm, while the flex sensor determines the flexion of the fingers. These sensors are placed in a specific position on the glove to obtain correct data when the glove is used. The glove has two modes, which are pencil grip mode and object grip mode. The sensors determine which mode the glove is in depending on the gesture made. The glove is examined using a pencil and a cylindrical object to evaluate the strength of the grip. After gripping the object or pencil, the system evaluates the force applied using the sensors. This data is transferred to a computer for further analysis using a trained model. The model was able to achieve an accuracy of 90.8%.
Feature selection of unbalanced breast cancer data using particle swarm optimization Amal Elnawasany; Mohamed Abd Allah Makhlouf; BenBella Tawfik; Hamed Nassar
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4951-4959

Abstract

Breast cancer is one of the significant deaths causing diseases of women around the globe. Therefore, high accuracy in cancer prediction models is vital to improving patients’ treatment quality and survivability rate. In this work, we presented a new method namely improved balancing particle swarm optimization (IBPSO) algorithm to predict the stage of breast cancer using unbalanced surveillance epidemiology and end result (USEER) data. The work contributes in two directions. First, design and implement an improved particle swarm optimization (IPSO) algorithm to avoid the local minima while reducing USEER data’s dimensionality. The improvement comes primarily through employing the cross-over ability of the genetic algorithm as a fitness function while using the correlation-based function to guide the selection task to a minimal feature subset of USEER sufficiently to describe the universe. Second, develop an improved synthetic minority over-sampling technique (ISMOTE) that avoid overfitting problem while efficiently balance USEER. ISMOTE generates the new objects based on the average of the two objects with the smallest and largest distance from the centroid object of the minority class. The experiments and analysis show that the proposed IBPSO is feasible and effective, outperforms other state-of-the-art methods; in minimizing the features with an accuracy of 98.45%.
Optimization of fuzzy photovoltaic maximum power point tracking controller using chimp algorithm Ammar Al-Gizi; Abbas Hussien Miry; Mohanad A. Shehab
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4549-4558

Abstract

In this paper, a photovoltaic (PV) fuzzy maximum power point tracking (MPPT) method optimized by the chimp algorithm is presented. The fuzzy logic controller (FLC) of seven triangular membership functions (MFs) is used. The optimization fitness function is composed of transient and steady-state indices under different irradiation and temperature operating conditions. By using MATLAB package, the performance of optimized method is examined and compared with asymmetrical FLC and well-known perturb and observe (P&O) tracking methods at different operating conditions in terms of: transient rising time (tr) and energy yield during 30 s. Moreover, the tracking methods are also compared in terms of the fitness function value. From the comparison of simulation results, a more energy can be harvested by using the proposed optimized tracking method compared to the other methods. Consequently, at the various operating conditions, the proposed method can be used as a more reliable tracking method for PV systems.
Ambulance detection for smart traffic light applications with fuzzy controller Robinson Jimenez-Moreno; Javier Eduardo Martinez Baquero; Luis Alfredo Rodriguez Umaña
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4876-4882

Abstract

In the development of intelligent cities, the automation of vehicular mobility is one of the strong points of research, where intelligent traffic lights stand out. It is essential in this field to prioritize emergency vehicles that can help save lives, where every second counts in favor of the transfer of a patient or injured person. This paper presents an artificial intelligence algorithm based on two stages, one is the recognition of emergency vehicles through a ResNet-50 and the other is a fuzzy inference system for timing control of a traffic light, both lead to an intelligent traffic light. An application of traffic light vehicular flow control for automatic preemption when detecting emergency vehicles, specifically ambulances, is oriented. The training parameters of the network, which achieves 100% accuracy with confidence levels between 65% with vehicle occlusion and 99% in direct view, are presented. The traffic light cycles are able to extend the green time of the traffic light with almost 50% in favor of the road that must yield the priority, in relation to not using the fuzzy inference system.
Smart agriculture for optimizing photosynthesis using internet of things and fuzzy logic Abdul Latief Qohar; Suharjito Suharjito
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5467-5480

Abstract

Photosynthesis is a process that plants need. Plant growth requires sunlight to carry out photosynthesis. At night photosynthesis cannot be carried out by plants. This research proposes an internet of things (IoT) model that can work intelligently to maximize photosynthesis and plant growth using fuzzy logic. The plants used in this research are mustard plants because mustard plants are plants that have broad leaves and require more photosynthesis. The outputs of this proposed model are the activation of light emitting diodes (LED) lights and automatic watering based on input sensors such as soil moisture, temperature, and light intensity which are processed with fuzzy logic. The results show that the use of the IoT model that has been proposed can provide faster and better growth of mustard plants compared with mustard plants without an IoT system and fuzzy logic. This result is also strengthened by comparing the t-test between the two groups, with a significant 95% confidence level. The proposed model in this research is also compared with similar research models carried out previously. This research resulted in a plant height difference of 30.43% higher than the previous research. So, it can conclude that the proposed model can accelerate the growth of mustard plants.
An efficient lightweight key exchange algorithm for internet of things applications Fasila Kasfa Ali; Sheena Mathew
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5609-5618

Abstract

Internet of things (IoT) gained wide popularity in recent years, and this is proved by tremendous increase in use of IoT applications worldwide. Distributed IoT applications can be implemented securely with the support of blockchain. By default, blockchain will ensure authentication of involved entities as well as integrity of data. Due to storage restrictions, use of hybrid system is preferred, and this involves cloud server for storage and blockchain for other functionalities. Data kept in cloud has to be encrypted by a strong encryption algorithm. Even though core security objectives are achieved, it is necessary to provide a secure method to exchange the key. Since, the key is the backbone of a security algorithm, protection of the key has to be ensured. In this work, an algorithm is proposed to provide a no-share key exchange between two communicating parties in a resource constrained environment. The same was implemented and compared with conventional key sharing algorithms. Security analysis was formally conducted by using widely accepted automated validation of internet security protocols and applications (AVISPA) tool and the proposed method proved to be secure.

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