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Indonesian Journal of Electrical Engineering and Informatics (IJEEI)

IJEEI
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Published by IAES Indonesia Section and Partners

ISSN : 20893272 EISSN : - DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

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.

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Articles 5 Documents

Search results for , issue "Vol 2, No 1: March 2014" : 5 Documents clear

A Comparison of Routing Protocol for WSNs: Redundancy Based Approach A Comparison of Routing Protocol for WSNs: Redundancy Based Approach Anand Prakash
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 2, No 1: March 2014
Publisher : IAES Indonesian Section

Wireless Sensor Networks (WSNs) with their dynamic applications gained a tremendous attention of researchers. Constant monitoring of critical situations attracted researchers to utilize WSNs at vast platforms. The main focus in WSNs is to enhance network localization as much as one could, for efficient and optimal utilization of resources. Different approaches based upon redundancy are proposed for optimum functionality. Localization is always related with redundancy of sensor nodes deployed at remote areas for constant and fault tolerant monitoring. In this work, we propose a comparison of classic flooding and the gossip protocol for homogenous networks which enhances stability and throughput quiet significantly.

Simplified Multimodal Biometric Identification Abhijit Shete; Kavita Tewari
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 2, No 1: March 2014
Publisher : IAES Indonesian Section

Multibiometric systems are expected to be more reliable than unimodal biometric systems for personal identification due to the presence of multiple, fairly independent pieces of evidence e.g. Unique Identification Project "Aadhaar" of Government of India. In this paper, we present a novel wavelet based technique to perform fusion at the feature level and score level by considering two biometric modalities, face and fingerprint. The results indicate that the proposed technique can lead to substantial improvement in multimodal matching performance. The proposed technique is simple because of no preprocessing of raw biometric traits as well as no feature and score normalization.

Determination of Coil Inductances Cylindrical Iron Nucleus Azeddine Mazouz; Djemai Hidjazi; Aziz Chaghi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 2, No 1: March 2014
Publisher : IAES Indonesian Section

The paper describes the investigation and development of a structure and performance characteristics of a coil iron nucleus cylindrical (C.I.N.C). The coil iron nucleus cylindrical is a nonlinear electro radio in which the moving of the nucleus in a sense or in other causes change in inductance and can reach extreme values at the superposition of nucleus and coil centers. The variation of the inductance and the degree of freedom of movement of the nucleus can lead to a device with electromechanical conversion The aim of this paper is the determination and visualization of self inductance and mutual of the (C.I.N.C) based on geometric dimensions and the displacement of the nucleus.

Backpropagation Neural Network Modeling for Fault Location in Transmission Line 150 kV Azriyenni Azriyenni; M.W. Mustafa; D.Y. Sukma; M.E. Dame
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 2, No 1: March 2014
Publisher : IAES Indonesian Section

In this topic research was provided about the backpropagation neural network to detect fault location in transmission line 150 kV between substation to substation. The distance relay is one of the good protective device and safety devices that often used on transmission line 150 kV. The disturbances in power system are used distance relay protection equipment in the transmission line. However, it needs more increasing large load and network systems are increasing complex. The protection system use the digital control, in order to avoid the error calculation of the distance relay impedance settings and spent time will be more efficient. Then backpropagation neural network is a computational model that uses the training process that can be used to solve the problem of work limitations of distance protection relays. The backpropagation neural network does not have limitations cause of the impedance range setting. If the output gives the wrong result, so the correct of the weights can be minimized and also the response of galat, the backpropagation neural network is expected to be closer to the correct value. In the end, backpropagation neural network modeling is expected to detect the fault location and identify operational output current circuit breaker was tripped it. The tests are performance with interconnected system 150 kV of Riau Region.

Adaptive Functional-Based Neuro-Fuzzy-PID Incremental Controller Structure Ashraf Ahmed Fahmy; Abdel Ghany Mohamed Abdel Ghany
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 2, No 1: March 2014
Publisher : IAES Indonesian Section

This paper presents an adaptive functional-based Neuro-fuzzy-PID incremental (NFPID) controller structure that can be tuned either offline or online according to required controller performance. First, differential membership functions are used to represent the fuzzy membership functions of the input-output space of the three term controller. Second, controller rules are generated based on the discrete proportional, derivative, and integral function for the fuzzy space. Finally, a fully differentiable fuzzy neural network is constructed to represent the developed controller for either offline or online controller parameter adaptation. Two different adaptation methods are used for controller tuning, offline method based on controller transient performance cost function optimization using Bees Algorithm, and online method based on tracking error minimization using back-propagation with momentum algorithm. The proposed control system was tested to show the validity of the controller structure over a fixed PID controller gains to control SCARA type robot arm.

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