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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 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. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 2,901 Documents
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Adaptation of stochasticity into activation function of deep learning for stock price forecasting Patrick Vincent, Assunta Malar; Salleh, Hassilah
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.4987

Abstract

Stock market is an example of a stochastic environment in the real world. multilayer perceptron (MLP) is often applied to forecast stock price. However, it is widely used to approximate the input-output mapping deterministically. Hence, this study aims to adapt stochasticity into MLP by introducing the Gaussian process into the sigmoid activation function. In addition, the adapted activation function incorporates Roger-Satchell and Yang-Zhang volatity estimators. Besides, the stochastic activation function was considered as a hyperparameter by applying it either only in training time or in both testing and training time. The stochastic multilayer perceptron (S-MLP) is then applied to forecast one day's highest stock price of eight constituents in FTSE Bursa Malaysia KLCI (FBMKLCI). The result shows that the proposed network is inferior in comparison to MLP except for several constituents. In addition, S-MLP with stochastic activation function during both the training and testing time performs better compared to the presence of stochastic activation function in S-MLP during training time only.
Multi-objective metaheuristic optimization algorithms for wrapper-based feature selection: a literature survey Anitha Gopalakrishnan; Vinodhini Vadivel
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4757

Abstract

In the data mining and machine learning (ML) discipline, feature selection problem is considered among many researchers in the recent times. Feature selection process targets to minimize feature set number and maximize performance accuracy by identifying optimal features. Multiple objectives are considered while identifying the optimal feature hence multi-objective metaheuristic optimization algorithms (MOMOAs) are applied. In this study, literature review is performed MOMOAs-for solving wrapper feature selection problem (WFS). The literature review for solving WFS problem and discuss the challenges faced by the researchers in solving the feature selection problem. The literature review is performed on all relevant studies published in the last 12 years [2009-2022]. A detailed overview of the feature selection preliminaries, MOMOAs-WFS, role of the classifier in feature selection problem are presented. The outcome of this literature review is to highlight the existing works related to WFS problem using MOMOAs. Finally, the research areas for improvement are identified and emphasized for the scientists to survey in the field of MOMOAs.
Accelerated thermal aging of Kraft papers impregnated with dielectric liquids Imran Sutan Chairul; Norazhar Abu Bakar; Sharin Ab Ghani; Mohd Shahril Ahmad Khiar; Nor Hidayah Rahim; Syahrun Nizam Md Arshad@Hashim
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4336

Abstract

Accelerated thermal aging was conducted on Kraft papers impregnated with mineral insulating oil (MO) and palm insulating oil (PO), and the effect of aging time on the oils and Kraft papers was observed. Each sample consisted of insulating oil, dried Kraft paper, and weighed metal catalysts (copper, iron, zinc, and aluminum) in a bottle. Prior to aging, the bottles were left for 24 h at room temperature for impregnation to take place. The thermal aging experiments were carried out at 130 °C for 250, 500, and 750 h. The properties of the MO and PO (moisture content, acidity, and ultraviolet-visible absorption spectra) and the properties of the Kraft papers (tensile strength and colour) were determined. Results showed that the aged PO had higher moisture content compared with the aged MO. However, the Kraft papers impregnated with PO had better tensile strength after 750 h of aging, which may be attributed to the affinity of PO to moisture. This slows down the hydrolytic degradation mechanism. In terms of colour, the Kraft papers were darker than their original colour as the tensile strength decreased. To conclude, the Kraft paper impregnated with PO had higher tensile strength compared with those impregnated with MO.
Anti-windup modified proportional integral derivative controller for a rotary switched reluctance actuator Md Ghazaly, Mariam; Tee, Siau Ping; Zainal, Nasharuddin
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.6027

Abstract

Over the last decade, industrial applications and promising research domains including robotics and automotive engineering have adopted the rotary switched reluctance actuator (SRA). SRA's fault tolerance, simple, strong structure, and high-frequency operation make it popular. However, the SRA's nonlinear magnetic flux flow and saturation operation negate its benefits. Several control systems have been developed; however, they often need extensive mechanism models and advanced control theory, making them impracticable. This paper proposes a modified proportional integral derivative (PID) controller to evaluate the control performance, which comprises of PID controller with an anti-windup, a linearizer unit, and switching mechanism to activate the SRA phases. The linearizer unit aids to compensate for the nonlinear current-displacement relationship. The anti-windup element helps to halt the integral action during the starting motion. At the fully aligned position, 60°, the modified PID reduced positioning steady-state error by 4.3 times at 76.9%, overshoot by 48.8%, and settling time by 25.3%. Both the modified PID and conventional PID showed zero steady-state error at intermediate position, 70°, however the modified PID controller depicted an improved percentage overshoot by 54.5% and settling time by 74.5%. The results show that the modified PID outperforms conventional PID in transient response, steady-state error, overshoot, and settling time.
On the design of trust and mobility based evaluation for intelligent collaborative UAVs assisted VANETs Sami Abduljabbar Rashid; Ahmed Shamil Mustafa; Abdulkareem Dawah Abbas; Hamza Qasim Abdullah; Mohammed Jassim Mohammed
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5223

Abstract

In recent days, vehicles usage and speed are highly increased that leads to an increase in energy consumption, delay, and overhead in the network. In this paper, a novel trajectory is introduced to achieve maximum reliability namely trust and mobility-based evaluation for intelligent collaborative (TMIC)-UAVs assisted VANETs. Reactive multipath greedy routing protocol (RMGR) is the hybrid routing protocol and it is the combination of ad hoc on-demand multipath distance vector (AOMDV) with greedy geographic forwarding (GGF) which is used for routing in frequently changeable network topology. To protect the network from malfunctions, effective trust evaluation (ETE) is performed by calculating the direct trust and indirect trust. Finally, to achieve effective communication among the UAVs, hybrid optimization is performed which is the combination of the genetic algorithm (GA) and the crow swarm optimization (CSO) algorithm. For validation network simulator (NS3) is used and the results show that this approach achieves high energy efficiency, delivery ratio, and reduction in delay when compared with the earlier research.
Jumping particle swarm optimization algorithm framework for content-based image retrieval system Bassel, Atheer; Jameel, Mohammed; Saad, Mohammed Ayad
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5024

Abstract

Content-based image retrieval (CBIR) has been studied well in the last decades in numerous research fields such as medicine, journalism, and private life. Applications of CBIR have been widely employed in medical images due to their direct impact on human life. With continues growing of digital libraries, there is a need for an efficient method to retrieve images from large datasets. In this paper, a new method was developed for CBIR based on the jumping particle swarm optimization (JPSO) algorithm. The proposed algorithm represents a developed instant of particle swarm optimization (PSO). However, JPSO the approach does not consider the velocity components to guide particle movements in the problem space. Instead of relying on inertia and velocity, intermittently random jumps (moves) occur from one solution to another within the discrete search space. To test the performance of the proposed algorithm, three types of medical image databases were used in the experiment which are the endoscopy 100, dental 100, and 50 skull image databases. The results show that the proposed algorithm could achieve high accuracy in image extraction and retrieve the accurate image category compared with other research works.
Improve power quality of charging station unit using African vulture optimization algorithm Saleh Masoud Abdallah Altbawi; Saifulnizam Abdul Khalid; Ahmad Safawi Mokhtar; Rayan Hamza Alsisi; Zeeshan Ahmad Arfeen; Hussain Shareef; Mehreen Kausar Azam
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5717

Abstract

In recent years, there is growth in acceptance to consume fewer fossil fuels globally and the manufacturing of electric vehicles (EVs) has become more popular. However, the increase in the number of systems connected to the grid that contain EVs with a huge power capacity leads to unstable working in the power system. To assess the stability of the electric charging station several control approaches in AC part and DC parts during charging mode and discharging modes are tested. African vulture optimization algorithm (AVOA) has been utilized to tune the system controllers (proportional integral derivative (PID)/tilt integral derivative (TID) controllers). The superiority of AVOA is confirmed by comparing the performance with the genetic algorithm (GA). Two objective functions have been used i.e. integral time absolute error (ITAE) and integral square time error (ISTE). AVOA-tuned TID controllers using ISTE were found to be the best to contain the frequency deviations. The results have shown of the AC part and DC part is within an acceptable limit recommended by IEEE standard. Further, maximum peak overshoot, undershoot, and settle time obtained by AVOA-tuned PID and TID controllers are found the best. Finally, the improvement of the performance index obtained by AVOA over its counterpart GA is confirmed.
Complexity prediction model: a model for multi-object complexity in consideration to business uncertainty problems Syah, Rahmad B. Y.; Satria, Habib; Elveny, Marischa; K. M. Nasution, Mahyuddin
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5380

Abstract

In a competitive environment, the ability to rapidly and successfully scale up new business models is critical. However, research shows that many new business models fail. This research looks at hybrid methods for minimizing constraints and maximizing opportunities in large data sets by examining the multivariable that arise in user behavior. E-metric data is being used as assessment material. The analytical hierarchy process (AHP) is used in the multi-criteria decision making (MCDM) approach to identify problems, compile references, evaluate alternatives, and determine the best alternative. The multi-objectives genetic algorithm (MOGA) role analyzes and predicts data. The method is being implemented to expand the information base of the strategic planning process. This research examines business sustainability along two critical dimensions. First, consider the importance of economic, environmental, and social evaluation metrics. Second, the difficulty of gathering information will be used as a predictor for making long-term business decisions. The results show that by incorporating the complexity features of input optimization, uncertainty optimization, and output value optimization, the complexity prediction model (MPK) achieves an accuracy of 89%. So that it can be used to forecast future business needs by taking into account aspects of change and adaptive behavior toward the economy, environment, and social factors.
Limits of reactive power compensation of a doubly fed induction generator based wind turbine system Abdulabbas, Ali Kadhim; Alawan, Mazin Abdulelah; Shary, Diyah Kammel
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4968

Abstract

The doubly fed induction generator (DFIG) systems feature a significant amount of free power capacity that may be used for reactive power adjustment when they are put into practical use. This change, which is occasionally overlooked, is a significant one. Using DFIG systems for wind turbines (WT), this paper explored strategies for reducing and using reactive power. In order to investigate the power characteristic and how it is regulated in DFIG systems, a mathematical model for the steady-state performance of DFIG WT has been developed and presented. Here is a detailed derivation of the limiting range of DFIG's reactive power capacity as well as the physical constraints on reactive power output. The distribution of the DFIG WT at a distribution network's end is demonstrated by a simulation example. Within this simulation, reactive power management strategy, load fluctuation, and the change in wind speed are all taken into consideration. Due to the possibility of a rise in the voltage at the access point, can concluded that both acceptable and efficient to use DFIG WT's reactive power capabilities as an additional continuous reactive power source for effectiveness.
An improved transient performance boost converter using pseudo-current hysteresis control Boutaghlaline, Anas; El Khadiri, Karim; Tahiri, Ahmed
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5835

Abstract

This paper introduces an enhanced low transient voltage and fast transient response boost converter. It uses a hysteresis-controlled circuit fed by a voltage signal from a rail-to-rail current sensor, resulting in improved efficiency, and transient response. The converter is designed using Taiwan semiconductor manufacturing company (TSMC) 0.18 µm CMOS 1P6M technology, delivers an output voltage of 1.8 V while operating with an input voltage range of 0.5 V to 1 V and supports an output load current range of 10 to 100 mA. The key contributions of this paper are: i) introducing a new boost converter architecture employing pseudo-current hysteresis-controlled (PCHC) techniques, ii) incorporating voltage and current loops into the proposed architecture, and iii) demonstrating superior transient performance. Experimental measurements reveal a peak power efficiency of 98.6% at 10 mA and transient times of 15.4 µs and 11.8 µs for a step load change from 10 to 100 mA and back to 10 mA, respectively, with transient voltages of 51 mV. The presented boost converter outperforms in terms of performance, compared to previous works using the figure of merit (FOM) formula.

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