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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 101 Documents
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Search results for , issue "Vol 12, No 2: February 2014" : 101 Documents clear
An improved charge pump with suppressed charge sharing effect Na Bai
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

A differential charge pump with reduced charge sharing effect is presented. The current-steering topology is adopted for fast switching. A replica charge pump is added to provide a current path for the complementary branch of the master charge pump in the current switching. Through the replica charge pump, the voltage at the complementary node of the master charge pump keeps stable during switching, and the dynamic charge sharing effect is avoided. Apply the charge pump to a 4.8 GHz band integer-N PLL, the measured reference spur is -49.7dBc with a 4-MHz reference frequency. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.2983
Accord Ignition Diagnosis Based on Improved GA-BP Tie Wang; Chao Wang; Jing Wu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

BP neural network as a kind of intelligent method is widely used in fault diagnosis, due to the single BP neural network’s error is big, GA algorithm is often used in optimizing BP neural network, but the standard GA algorithm’s searching efficiency is low and it is easy to fall into local convergence. According to the characters of Accord car ignition diagnosis and BP neural network, this article puts forward an improved scheme of the standard GA algorithm optimizing BP net, calculate and analyze different simulation results gotten by MATLAB program. Through calculation: the single BP neural network’s convergence step number is 101, the final mean square error is 0.000997167; the convergence step number that standard GA algorithm optimizes the BP neural net is 83, the final mean square error is 0.000142126; the convergence step number that GA algorithm improved optimizes the BP neural net is 73, the final mean square error is 0.000137508. By the comparison, the improved GA algorithm has a better search efficiency and it’s computation can avoid falling into a local convergence. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3839
Review on the Studies and Advances of Machine Learning Approaches Yongqing Wang; Qingxiu Li
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Artificial intelligence is a frontier field of computer science, and achieved considerable progress in the past few decades. Being an important research branch of artificial intelligence, machine learning has been successfully applied to many fields in recent years, such as expert system, automatic reasoning, natural language processing, pattern recognition, computer vision, intelligent robots, and so on. This article comprehensively introduces the main strategies of machine learning, and summarizes the existing problems and challenges. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3635
Maximum Value Search and Polynomial Fit Metal Artifact Reduction Algorithm Li Yuanjin; Wang Tao
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Metal artifacts seriously degrade CT image quality, and even restrict the using of computed tomography imaging. In this paper, the authors propose a metal artifact reduction algorithm to suppress the metal artifacts in CT image. The metal artifact reduction algorithm, in this paper, includes six steps: coarse metal implant segmentation, nearly accurate metal object segmentation, forward projection, polynomial-based fit, adaptive scaling as well as final image reconstruction. Experiment on image showed that RMSEs between the corrected image using polynomial fit, nearest interpolation, linear interpolation and spline interpolation and ideal model image are 0.20912, 0.33252, 0.24257 and 0.26791, respectively. It has the potential to greatly improve the quality of CT image and suppress the metal artifacts. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3623
A New Naive Bayes Text Classification Algorithm Duan Li-guo; Di Peng; Li Ai-ping
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Aiming at the phenomenon that in text classification the calculation of prior probability is time-consuming and has little effect on the classification results and the error propagation of posterior probability affects the accuracy of classification, this paper improves the classical naïve bayes algorithm and proposes a new text classification algorithm which accelerates the speed by removing the calculation of prior probability and reduces the accuracy loss of error propagation by adding an amplification factor .The experiments prove that removing the calculation of prior probability can accelerate the classification speed obviously and has little effect on the classification accuracy, and adding an amplification factor in the calculation of posterior probability can reduce the effect of error propagation and improve the classification accuracy. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.4180 
Improved Direct Torque Double Closed-Loop Control Algorithm for Induction Motor Huaqiang ZHANG; Tong YAO; Shijun LUO
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

This paper presents an improved direct torque control (DTC) algorithm as compared to a traditional DTC scheme. In the traditional scheme, a pair of hysteresis comparators is used to control motor stator flux and electromagnetic torque. This causes a variable switching frequency which results in a high flux and torque ripples. To mitigate these issues, an improved DTC algorithm based on a double closed-loop is presented. Acting the induction motor as a control object, a mathematical model of the flux and torque based on proportional and integral (PI) controller in the double closed-loop is established. With the flux and the torque treated as control variables, a smooth and continuous vector control and a fast-response DTC are observed. By adopting this improved DTC algorithm, the simulation and experimental results indicate that the flux and the torque ripples reduced greatly. Additionally, the static and dynamic performances of the system are improved because of the mentioned scheme operating at a constant switching frequency. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.4329 
Energy demand forecasts based on improved Gray neural network algorithm Ying Jin Li; Fen Zhi Xu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Energy demand forecasting and energy consumption structure analysis were important foundation for energy planning and development of new energy, so energy forecasting result was required as close as possible to the actual value. To improve the prediction accuracy, this article combined back propagation (abbreviated bp) neural network and gray phase to build an improved gray neural network prediction method, and using genetic algorithms to optimize it. The experiment proved that this model has high prediction accuracy, and used it to predict the energy demand in Hebei Province, the results proved the validity of the model. Finally, the article also analyzed the energy structure and the development of new energy based on forecast results in Hebei Province. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3731
Multidisciplinary Multi-objective Optimization Method for Vehicle Crashworthiness Design Zhixia Jiang; Pinchao Meng; Tiandong Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

This paper proposes a multidisciplinary multi-objective optimization method for vehicle Crashworthiness design. Multi-objective optimization methods are discussed. Considering the objective functions with difference dimensions, we improve -method based on normalizes objective function. As the numerical example, the vehicle crashworthiness design problem is calculated, and we compare the results with SO method, interior point method and active-set method, where interior point method and active-set method are based the improved -method. Examples indicate that this algorithm has less number of iteration than the others. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3832
Adaptive Deployment Scheme and Multi-path Routing Protocol for WMSNs Enyan Sun; Xuanjing Shen; Haipeng Chen; Chuanyun Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Multi-path routing protocols have many advantages in wireless multimedia sensor networks. To succeed in setting up multiple paths in the wireless multimedia sensor network, the Adaptive Deployment Scheme of sensor Nodes which is based upon multi-path routing protocol (ADSN) is proposed in the paper. ADSN deploys the sensor nodes on the basis of the number of paths, camera nodes’ positions and the sink’s position etc. Compared to the uniform deployment scheme, ADSN can save 67% sensor nodes when setting up multiple paths. And it can avoid the hotspot area in the vicinity of the sink. Energy Equalization Multi-path Routing protocol (EEMR) can consume the energy of sensor nodes more evenly and extends the network lifetime compared to TPGF. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3820
Substation Fault Diagnosis Based on Rough Sets and Grey Relational Analysis Haiying Dong; Xiaonan Li; Zhanhong Wei
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

As the 750kV substation has the characteristics like incomplete information, uncertain diagnosis result and dual protection configuration, a fault diagnosis method of substation with redundant protection configuration based on rough sets and grey relational analysis is proposed. In this method, the diagnosis decision table which takes advantage of information about wave-recording devices and two protective devices is constructed and simplified, and the minimal reduction can be obtained by using knowledge acquisition method based on rough set; Based on the point, the comparative sequence and reference sequence is established. Through the use of grey relational analysis, the grey relational grade of attributes and failure rate of suspicious fault components is determined in the reduction table, and furthermore obtain a certain diagnosis result. The result shows that the proposed method is effective. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3636

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