Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Articles
20 Documents
Search results for
, issue
"Vol 8, No 1: March 2020"
:
20 Documents
clear
<![CDATA[Frequency Control of Microgrid with Renewable Generation using PID Controller based Krill Herd ]]>
<![CDATA[Mohamed Regad]]>;
<![CDATA[M'hamed Helaimi]]>;
<![CDATA[Rachid Taleb]]>;
<![CDATA[Ahmed M. Othman]]>;
<![CDATA[Hossam A.Gabbar]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1503.929 KB)
|
DOI: 10.52549/ijeei.v8i1.1291
<![CDATA[The main of this paper is to provide optimal control of a state microgrid system. The proposed configuration composes of renewable generation systems such as solar photovoltaic system and wind turbine generator with a Diesel Engine Generator and Fuel-Cell. An Aqua electrolyzer and other energy storage systems such as battery and flywheel are also used in the proposed microgrid. A standard PID (Proportional Integral Derivative) controller scheme is introduced whose its parameters are determined using different optimizations algorithm such as Algorithm Genetic, Particle Swarm Optimization, and Krill Herd algorithm for minimizing frequency and power deviations, in order to enhance the operation of this system. The PID controller gains are optimized by resolving an objective function. The simulation results are shown, and given that the Krill Herd algorithm improves the performance of the system in comparison with GA and PSO based on PID. The efficiency of the system is improved.]]>
<![CDATA[Adaptive Parameter Control Strategy for Ant-Miner Classification Algorithm ]]>
<![CDATA[Hayder Naser Khraibet Al-Behadili]]>;
<![CDATA[Rafid Sagban]]>;
<![CDATA[Ku Ruhana Ku-Mahamud]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (908.687 KB)
|
DOI: 10.52549/ijeei.v8i1.1423
<![CDATA[Pruning is the popular framework for preventing the dilemma of overfitting noisy data. This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-AntMiner. A key aspect of this algorithm is the selection of an appropriate number of terms to be included in the classification rule. ACS-AntMiner introduces a new parameter called importance rate (IR) which is a pre-pruning criterion based on the probability (heuristic and pheromone) amount. This criterion is responsible for adding only the important terms to each rule, thus discarding noisy data. The ACS algorithm is designed to optimize the IR parameter during the learning process of the Ant-Miner algorithm. The performance of the proposed classifier is compared with related ant-mining classifiers, namely, Ant-Miner, CAnt-Miner, TACO-Miner, and Ant-Miner with a hybrid pruner across several datasets. Experimental results show that the proposed classifier significantly outperforms the other ant-mining classifiers.]]>
<![CDATA[Genetic Algorithm-Based Approach for Minimising Losses in Substrate-Integrated Waveguide ]]>
<![CDATA[Nur Hidayah Mansor]]>;
<![CDATA[Razi Abdul-Rahman]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (711.651 KB)
|
DOI: 10.52549/ijeei.v8i1.1532
<![CDATA[The transitions in air-filled substrate-integrated waveguide (SIW) are studied here for millimetre-wave applications. A good design of an air-filled SIW (AFSIW) must allow for minimum losses in its interconnects between the air-filled and dielectric-filled regions of the SIW. This paper assesses the influence of the geometry of transition taper in an AFSIW on the return and insertion losses using full-wave analysis of a complete AFSIW structure. The data from the return and transmission losses provide a basis in the optimisation of the design of the transition tapers. The optimisation approach uses the multi-objective genetic algorithm (GA) with full-wave analysis to find an optimum profile of the transition. Defining the profile of the transition taper with a clamped cubic spline as a phenotype, the developed procedure shows that further losses are possible within the prescribed frequency bands. Furthermore, the length of the transition taper can be significantly reduced while maintaining an optimal quality of signal transmission in the transition. The simulation results show the efficacy of the proposed strategy where the optimal taper geometry is shown to provide a wider band of operating frequencies with lower return loss compared to a more established taper geometry.]]>
<![CDATA[Noise Cancellation Employing Adaptive Digital Filters for Mobile Applications ]]>
<![CDATA[AM Prasanna Kumar]]>;
<![CDATA[SM Vijaya]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (871.906 KB)
|
DOI: 10.52549/ijeei.v8i1.1155
<![CDATA[The persistent improvement of the hybrid adaptive algorithms and the swift growth of signal processing chip enhanced the performance of signal processing technique exalted mobile telecommunication systems. The proposed Artificial Neural Network Hybrid Back Propagation Adaptive Algorithm (ANNHBPAA) for mobile applications exploits relationship among the pure speech signal and noise corrupted signal in order to estimate of the noise. An adaptive linear system responds for changes in its environment as it is operating. Linear networks are gets adjusted at each time step based on new input and target vectors can find weights and biases that minimize the networks sum squared error for recent input and target vectors. Networks of this kind are quite oftenly used for error cancellation, speech signal processing and control systems. Noise in an audio signal has become major problem and hence mobile communication systems are demanding noise-free signal. In order to achieve noise-free signal various research communities have provided significant techniques. Adaptive noise cancellation (ANC) is a kind of technique which helps in estimation of un-wanted signal and removes them from corrupted signal. This paper introduces an Adaptive Filter Based Noise Cancellation System (AFNCS) that incorporates a hybrid back propagation learning for the adaptive noise cancellation in mobile applications. An extensive study has been made to explore the effects of different parameters, such as number of samples, number of filter coefficients, step size and noise level at the input on the performance of the adaptive noise cancelling system. The proposed hybrid algorithm consists all the significant features of Gradient Adaptive Lattice (GAL) and Least Mean Square (LMS) algorithms. The performance analysis of the method is performed by considering convergence complexity and bit error rate (BER) parameters along with performance analyzed with varying some parameters such as number of filter coefficients, step size, number of samples and input noise level. The outcomes suggest the errors are reduced significantly when the numbers of epochs are increased. Also incorporation of less hidden layers resulted in negligible computational delay along with effective utilization of memory. All the results have been obtained using computer simulations built on MATLAB platform]]>
<![CDATA[Improvement of alzheimer disease diagnosis accuracy using ensemble methods ]]>
<![CDATA[Mohammed Abdullah Al-Hagery]]>;
<![CDATA[Ebtehal Ibrahim Al-Fairouz]]>;
<![CDATA[Norah Ahmed Al-Humaidan]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (80.682 KB)
|
DOI: 10.52549/ijeei.v8i1.1321
<![CDATA[Nowadays, there is a significant increase in the medical data that we should take advantage of that. The application of the machine learning via the data mining processes, such as data classification depends on using a single classification algorithm or those complained as ensemble models. The objective of this work is to improve the classification accuracy of previous results for Alzheimer disease diagnosing. The Decision Tree algorithm with three types of ensemble methods combined, which are Boosting, Bagging and Stacking. The clinical dataset from the Open Access Series of Imaging Studies (OASIS) was used in the experiments. The experimental results of the proposed approach were better than the previous work results. Where the Random Forest (Bagging) achieved the highest accuracy among all algorithms with 90.69%, while the lowest one was Stacking with 79.07%. All these results generated in this paper are higher in accuracy than that done before.]]>
<![CDATA[Performance realization of Bridge Model using Ethernet-MAC for NoC based system with FPGA Prototyping ]]>
<![CDATA[SP Guruprasad]]>;
<![CDATA[BS Chandrasekar]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (522.921 KB)
|
DOI: 10.52549/ijeei.v8i1.1216
<![CDATA[The System on Chip (SoC) integrates the number of processing elements (PE) with different application requirements on a single chip. The SoC uses bus-based interconnection with shared memory access. However, buses are not scalable and limited to particular interface protocol. To overcome these problems, The Network on Chip (NoC) is an emerging interconnect solution with a scalable and reliable solution over SoC. The bridge model is essential to communicate the NoC based system on SoC. In this article, a cost-effective and efficient bridge model with ethernet-MAC is designed and also the placement of the bride with NoC based system is prototyped on Artix-7 FPGA. The Bridge model mainly contains FIFO modules, Serializer and de-serializer, priority-based arbiter with credit counter, packet framer and packet parser with Ethernet-MAC transceiver Module. The bridge with a single router and different sizes of the NoC based systems with mesh topology are designed using adaptive-XY routing. The performance metrics are evaluated for bridge with NoC in terms of average latency and maximum throughput for different Packet Injection Rate (PIR).]]>
<![CDATA[Real-time Implementation of Space Vector Modulation using Arduino as a Low-cost Microcontroller for Three-phase Grid-connected Inverter ]]>
<![CDATA[Amal Satif]]>;
<![CDATA[Laamari Hlou]]>;
<![CDATA[Abdelkarim Zemmouri]]>;
<![CDATA[Hamad Dahou]]>;
<![CDATA[Rachid Elgouri]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1069.486 KB)
|
DOI: 10.52549/ijeei.v8i1.1207
<![CDATA[This work aims to facilitate the approach of a promising and fascinating technology, which is the photovoltaic (PV) energy, concerning the integration of PV systems to the utility grid from the control/synchronization point of view. Within this context, this paper gives a performance analysis of modeling and driving a two-level three-phase grid-connected PV system, in order to reduce the variations in frequency and phase, as a result, the synchronization between the inverter and the utility grid is accomplished and the correct function of the inverter is performed. MATLAB/Simulink software was utilized to develop the model of the suggested control algorithms. Then, as an interfacing device between the software and the inverter, the Arduino UNO microcontroller is proposed as a low-cost and simplified method to control the three-phase grid-connected inverter]]>
<![CDATA[Sensorless Predictive Direct Power Control PDPC_SVM For PWM Converter Under Different Input Voltage Conditions ]]>
<![CDATA[Ismail Boukhechem]]>;
<![CDATA[Ahcen Boukadoum]]>;
<![CDATA[Lahcene Boukelkoul]]>;
<![CDATA[Houssam Eddine Medouce]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (783.82 KB)
|
DOI: 10.52549/ijeei.v8i1.1542
<![CDATA[In this paper, a new virtual flux (VF) based predictive direct power control (VF_PDPC) applied for three-phase pulse width modulation (PWM) rectifier is proposed. The virtual flux estimation is performed using a pure integrator in series with a new adaptive algorithm in order to cancel dc offset and harmonic distortions in the estimated VF. The introduced structure is able to produce two virtual flux positive sequence components orthogonal output signals under unbalanced and distorted voltage conditions. The main features of the proposed virtual flux estimator are, it's simple structure, accuracy, and fast VF estimation over the excited integrators. Therefore, the estimated VF is then used for robust sensorless VF-PDPC with a constant switching frequency using space vector modulation (SVM) and tested through numerical simulations. The instantaneous active and reactive powers provided by orthogonal (VF) positive sequence components are directly controlled. More importantly, this configuration gives quasi-sinusoidal and balanced current under different input voltage conditions without using the power compensation methods. The results of the simulation confirmed the validity of the proposed virtual flux algorithm and demonstrated excellent performance under different input voltage conditions, complete rejection of disturbances.]]>
<![CDATA[A Fast and Accurate Object Detection Algorithm on Humanoid Marathon Robot ]]>
<![CDATA[Eko Rudiawan Jamzuri]]>;
<![CDATA[Hanjaya Mandala]]>;
<![CDATA[Jacky Baltes]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (957.107 KB)
|
DOI: 10.52549/ijeei.v8i1.1960
<![CDATA[This paper introduces a fast and accurate object detection algorithm based on a convolutional neural network for humanoid marathon robot applications. The algorithm is capable of operating on a low-performance CPU without relying on the GPU or hardware accelerator. A new region proposal algorithm, based on color segmentation, is proposed to extract a region containing a potential object. As a classifier, the convolution neural network is used to predict object classes from the proposed region. In the training phase, the classifier is trained with an Adam optimizer to minimize the loss function, using datasets collected from humanoid marathon competitions and diversified using image augmentation. An NVIDIA GTX 1070 training machine, with 500 batch images per epoch and a learning rate of 0.001, required 12 seconds to minimize the loss value below 0.0374. In the accuracy evaluation, the proposed method successfully recognizes and localizes three classes of marker with a training accuracy of 99.929%, validation accuracy of 99.924%, and test accuracy of 98.821%. As a real-time benchmark, the algorithm achieves 41.13 FPS while running on a robot computer with Intel i3-5010U CPU @ 2.10GHz.]]>
<![CDATA[Research of the Sensitivity of the Quantized Coefficients of a Digital Bandpass Filters with Frequency Sampling ]]>
<![CDATA[Rybka Serhii Volodуmуrovуch]]>;
<![CDATA[Korolov Andrii Pavlovуch]]>;
<![CDATA[Varava Ivan Andriiovуch]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (652.449 KB)
|
DOI: 10.52549/ijeei.v8i1.1552
<![CDATA[The article is devoted to the applied research of the dependence of the influence of the transfer function quantized coefficients of digital bandpass filters with frequency sampling on its attenuation characteristic. It is shown that only the coefficients, which depend on the frequency, when quantized, significantly distort the shape of the attenuation characteristic. Such coefficients in the article are called frequency coefficients. The magnitudes of the deviations of the quantized frequency coefficients from the calculated values at different values of the bit depth are analyzed. The attenuation characteristics of the digital comb of bandpass filters based on frequency sampling with calculated and quantized coefficients are analyzed. Practical recommendations are offered to minimize the influence of frequency coefficients quantization errors at the stage of solving the task of approximation of digital bandpass filters with frequency sampling. The result will be an optimal choice of the minimum number bit of the processors or programmable logic integrated circuits (FPGA), to be used for the implementation of digital bandpass filters with frequency sampling.]]>
