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Bulletin of Electrical Engineering and Informatics

EEI
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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.

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Articles 2,901 Documents

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Inductive Generalization in Logical Inference and Techniques to Estimate It Boris A. Kulik; Alexander Ya. Fridman
Bulletin of Electrical Engineering and Informatics Vol 3, No 3: September 2014
Publisher : Institute of Advanced Engineering and Science

The paper presents a novel approach to problems of deductive reasoning in frames of n-tuple algebra (NTA) earlier developed by the authors. Investigations of such problems let us determine the minimal consequence in logical inference and develop techniques to find it. Besides, we have proved that many formally correct consequences are inductive generalizations of this minimal consequence. An NTA-based method is proposed to obtain a numerical estimation for the degree of such an inductive generalization. In particular, it becomes possible to predict the number of consequences for a given system of premises and the share of a minimal consequence in a universe.

Neural Network Navigation Technique for Unmanned Vehicle Boumediene Selma; Samira Chouraqui
Bulletin of Electrical Engineering and Informatics Vol 3, No 3: September 2014
Publisher : Institute of Advanced Engineering and Science

Using a neural network (ANN) for the brain, we want a vehicle to drive by itself avoiding obstacles. We accomplish this by choosing the appropriate inputs/outputs and by carefully training the ANN. We feed the network with distances of the closest obstacles around the vehicle to imitate what a human driver would see. The output is the acceleration and steering of the vehicle. We also need to train the network with a set of strategic input-output. The result is impressive, for a couple of neurons! The unmanned vehicle (UV) drives around avoiding obstacles, but some improvement or modification can be done to make this software work for a specific purpose.

Leakage Analysis and Solution of the RFID Analog Front-END Lin Changlong; Ma Shiliang; Lu Xin; Sun Xinzhuo; Chen Yao; Liang Ke
Bulletin of Electrical Engineering and Informatics Vol 3, No 3: September 2014
Publisher : Institute of Advanced Engineering and Science

The identification and modeling of different leakage components are very important for estimation and reduction of leakage power, especially low-power applications, such as RFID chip. This paper proposes a theory about leakage mechanism of RFID chip and proves the theory. The one contribution of the paper is the proposed theory about leakage mechanism of RFID chip. The other contribution is that it proves the differences between tape-out verification results and computer simulation results and that to what degree the differences occur for different circuits. And when the source potential is much lower than the substrate potential, tape-out verification results and computer simulation results have larger differences. The test results show that the actual leakage power increases 26.3 times compares with the computer simulation results’ when the source potential is -750mV.

Optimal PID Controller designing for voltage control of Fuel Cell Omid Khezri; Seyed Jalal Seyed Shenava
Bulletin of Electrical Engineering and Informatics Vol 3, No 4: December 2014
Publisher : Institute of Advanced Engineering and Science

This paper is proposed a PID optimal controller in order to control of one of the most important types of fuel cell, namely proton exchange membrane fuel cell (PEMFC). At first, the introducing and implementation of PEMFC is present and next, during system load variations the proposed controller is designed. The controller should be designed against the load variations for keeping in a fixed value of Fuel cell output voltage. Here, the PID Controller is used which its coefficients are optimized based on Invasive Weed Optimization (IWO). In order to use this algorithm, at first, problem is written as an optimization problem which includes the objective function and constraints, and then to achieve the most desirable controller, IWO algorithm is applied to solve the problem. Simulation results are done for various loads in time domain, and the results show the efficiency of the proposed controller in contrast to the previous controllers.

Design of Quadratic Optimal Regulator System for State Space Model of Single phase Inverter both in Standalone and Gridtie Modes Nagulapati Kiran; V.Anil Kumar; Dhanamjaya Appa Rao
Bulletin of Electrical Engineering and Informatics Vol 3, No 4: December 2014
Publisher : Institute of Advanced Engineering and Science

Since in 3-phase systems, the reliability of 3-phase Inverter is not good, under such situations Paralleled Inverter Systems are used. Parallel Inverter operation has a major role in uninterruptible power system (UPS) applications. Most of the standalone inverter systems use a LC filter and proportional-integral (PI) controller in their control loops. When connecting the paralleled inverters to utility grids, the capacitor becomes redundant and thus either a pure inductor or an LCL filter can be used as inverter output stage. Compared with the L filter, the LCL filter is more attractive because it cannot only provide higher harmonics attenuation with same inductance value, but also allow inverter to operate both in standalone and grid-tie modes, which makes it a universal inverter for distributed generation applications. Output of Inverter should always be checked. In this paper State Space Model of Single phase Inverter is analysis in two modes which are: a) Grid-tie Mode b) Standalone Mode.A Quadratic Optimal Regulator System is designed and its unit step response is obtained to validate whether the whole system (inverter system along with designed QOR) is a stable system or not. This is done using MATLAB Program.

Analysis on the voltage stability on transmission network with PV interconnection Karmila Kamil; Muhammad Amirul Ashraf Ab Rahman; Chong Kok Hen; Halimatun Hashim; Mohd Helmi Mansor
Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Voltage stability means the ability of the power system network to maintain steady-state voltage value at all buses in the system under normal condition and after being subjected to a disturbance. This research highlights the effect of solar photovoltaic (PV) as the subject of disturbance to the network system as this kind of energy source has emerged towards higher level of integration into the national grid. High penetration of solar PV into the grid may cause several issues of stability and security to the system particularly effecting the normal voltage and line overloading. This research is focused on the simulation of power flow to study the transmission network behavior with and without the solar PV interconnection. To accomplish the research objectives, the network system will be modelled in a software known as Power System Simulator for Engineering (PSSE). The simulation result will be discussed and analyzed using Voltage Stability Indices (VSI) to prove and strengthen the theory behind the literature review.

Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system Nur Ainna Shakinah Abas; Ismail Musirin; Shahrizal Jelani; Mohd Helmi Mansor; Naeem M. S. Honnoon; Muhammad Murtadha Othman
Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

This paper presents the optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simulation is used to find the random number of locations of MDGs. This involved the testing of the proposed technique on IEEE 69-bus distribution test system. It is found that the proposed approach successfully solved the MDGs installation problem by reducing the power losses and improving the minimum voltage of the distribution system.

A regression approach for prediction of Youtube views Rui, Lau Tian; Afif, Zehan Afizah; Saedudin, R. D. Rohmat; Mustapha, Aida; Razali, Nazim
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

YouTube has grown to be the number one video streaming platform on Internet and home to millions of content creator around the globe. Predicting the potential amount of YouTube views has proven to be extremely important for helping content creator to understand what type of videos the audience prefers to watch. In this paper, we will be introducing two types of regression models for predicting the total number of views a YouTube video can get based on the statistic that are available to our disposal. The dataset we will be using are released by YouTube to the public. The accuracy of both models are then compared by evaluating the mean absolute error and relative absolute error taken from the result of our experiment. The results showed that Ordinary Least Square method is more capable as compared to the Online Gradient Descent Method in providing a more accurate output because the algorithm allows us to find a gradient that is close as possible to the dependent variables despite having an only above average prediction.

An improvised similarity measure for generalized fuzzy numbers Daud Mohamad; Noorlisa Sara Adlene Ramlan; Sharifah Aniza Sayed Ahmad
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Similarity measure between two fuzzy sets is an important tool for comparing various characteristics of the fuzzy sets. It is a preferred approach as compared to distance methods as the defuzzification process in obtaining the distance between fuzzy sets will incur loss of information. Many similarity measures have been introduced but most of them are not capable to discriminate certain type of fuzzy numbers. In this paper, an improvised similarity measure for generalized fuzzy numbers that incorporate several essential features is proposed. The features under consideration are geometric mean averaging, Hausdorff distance, distance between elements, distance between center of gravity and the Jaccard index. The new similarity measure is validated using some benchmark sample sets. The proposed similarity measure is found to be consistent with other existing methods with an advantage of able to solve some discriminant problems that other methods cannot. Analysis of the advantages of the improvised similarity measure is presented and discussed. The proposed similarity measure can be incorporated in decision making procedure with fuzzy environment for ranking purposes.

Comparative analysis on bayesian classification for breast cancer problem Wan Nor Liyana Wan Hassan Ibeni; Mohd Zaki Mohd Salikon; Aida Mustapha; Saiful Adli Daud; Mohd Najib Mohd Salleh
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

The problem of imbalanced class distribution or small datasets is quite frequent in certain fields especially in medical domain. However, the classical Naive Bayes approach in dealing with uncertainties within medical datasets face with the difficulties in selecting prior distributions, whereby parameter estimation such as the maximum likelihood estimation (MLE) and maximum a posteriori (MAP) often hurt the accuracy of predictions. This paper presents the full Bayesian approach to assess the predictive distribution of all classes using three classifiers; naïve bayes (NB), bayesian networks (BN), and tree augmented naïve bayes (TAN) with three datasets; Breast cancer, breast cancer wisconsin, and breast tissue dataset. Next, the prediction accuracies of bayesian approaches are also compared with three standard machine learning algorithms from the literature; K-nearest neighbor (K-NN), support vector machine (SVM), and decision tree (DT). The results showed that the best performance was the bayesian networks (BN) algorithm with accuracy of 97.281%. The results are hoped to provide as base comparison for further research on breast cancer detection. All experiments are conducted in WEKA data mining tool.

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