cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Imam Much Ibnu Subroto
Contact Email
imam@unissula.ac.id
Phone
-
Journal Mail Official
ijai@iaesjournal.com
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
IAES International Journal of Artificial Intelligence (IJ-AI)
Published by Institute of Advanced Engineering and Science
ISSN : 20894872     EISSN : 22528938     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering
IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like genetic algorithm, ant colony optimization, etc); reasoning and evolution; intelligence applications; computer vision and speech understanding; multimedia and cognitive informatics, data mining and machine learning tools, heuristic and AI planning strategies and tools, computational theories of learning; technology and computing (like particle swarm optimization); intelligent system architectures; knowledge representation; bioinformatics; natural language processing; multiagent systems; etc.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol 4, No 1: March 2015" : 5 Documents clear
Design and Development of an Agorithm for Prioritizing the Test Cases Using Neural Network as Classifier Amit Verma; simranjeet kaur
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 1: March 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (582.919 KB) | DOI: 10.11591/ijai.v4.i1.pp14-19

Abstract

Test Case Prioritization (TCP) has gained wide spread acceptance as it often results in good quality software free from defects. Due to the increase in rate of faults in software traditional techniques for prioritization results in increased cost and time. Main challenge in TCP is difficulty in manually validate the priorities of different test cases due to large size of test suites and no more emphasis are made to make the TCP process automate. The objective of this paper is to detect the priorities of different test cases using an artificial neural network which helps to predict the correct priorities with the help of back propagation algorithm. In our proposed work one such method is implemented in which priorities are assigned to different test cases based on their frequency. After assigning the priorities ANN predicts whether correct priority is assigned to every test case or not otherwise it generates the interrupt when wrong priority is assigned. In order to classify the different priority test cases classifiers are used. Proposed algorithm is very effective as it reduces the complexity with robust efficiency and makes the process automated to prioritize the test cases.
A Novel Neuro-Fuzzy Controller for Multilevel Renewable Energy System T PAVAN KUMAR; B N KARTHEEK
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 1: March 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (587.791 KB) | DOI: 10.11591/ijai.v4.i1.pp20-28

Abstract

Recently, Development and the utilization of single phase based multilevel inverters has been increased. This paper proposes concept based new topology based seven level inverter with less number of power electronics switches with utility grid connection. This proposed multilevel inverter operates with only eight power electronics switches at their fundamental frequency. This inverter produces seven level output from the input here we considered as a photovoltaic system. The cost, complexity, switching losses are small due to because of usage of less number of switches. The DC/DC converter receives input from which the three positive output voltages are generated and the multilevel inverter performs as a polarity reversal that provides both the positive and negative cycle output. For further enhancement in the output waveform, the filter circuit can be integrated in the output terminal of the multilevel inverter. This paper also proposed a concept of a neuro-fuzzy controller for controlling the seven level inverter. The simulation results are observed by means of MATLAB simulink toolbox.
Direct Field-Oriented Control Using Fuzzy Logic Type -2 for Induction Motor with Broken Rotor Bars Saad Belhamdi; Amar Goléa
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 1: March 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (782.859 KB) | DOI: 10.11591/ijai.v4.i1.pp29-36

Abstract

In the paper an analysis of the Direct Field Control Fuzzy logic type-2 of induction motor drive with broken rotor bars is presented. The simplicity of traditional regulators makes them popular and the most used solution in the nowadays industry. However, they suffer from some limitations and cannot deal with nonlinear dynamics and system parameters variation. In the literature, several strategies of adaptation are developed to alleviate these limitations. Artificial intelligent has found high application in most nonlinear systems same as motors drive. Because it has intelligence like human but there are no sentimental against human like angriness and.... Artificial intelligent is used for various points like approximation, control, and monitoring. Because artificial intelligent techniques can use as controller for any system without requirement to system mathematical model, it has been used in electrical drive control. With this manner, efficiency and reliability of drives increase and volume, weight and cost of them decrease.
Neuro Fuzzy Based Unified Power Quality Conditioner for Power Quality Improvement Fed Induction Motor Drive R. Saravanan; P.S. Manoharan
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 1: March 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (456.051 KB) | DOI: 10.11591/ijai.v4.i1.pp1-7

Abstract

The unified power quality conditioner (UPQC) plays an important role in the constrained delivery of electrical power from source to an isolated pool of load or from a source to the grid.  In this paper presents neuro fuzzy based unified power quality conditioner. The series converter is used to compensate voltage sag/swell compensation. The shunt converter is used to compensate reactive power compensation present in the linear and nonlinear load. The performance of neuro fuzzy and with artificial neural network controller is compared. This approach eliminates the total harmonic distortions efficiently. The performance of proposed system is analysed using Mat lab/Simulink.
A Fuzzy Logic Based DSTATCOM for Diesel Generation System for Load Compensation JACOB PRABHAKAR BUSI; SRINIVASARAO YELAVARTHI
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 1: March 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (521.929 KB) | DOI: 10.11591/ijai.v4.i1.pp8-13

Abstract

This paper proposes the concept of distributed static compensator for compensation of harmonics, unbalances and reactive powers. The main aim of this diesel electrical generator is to generate electrical power and transfer to the distribution point. The main problems occurred in this distribution systems are voltage distributions, interruptions and variations in distribution system also called as power quality problems. The FACTS controllers are classified into different types based on improvement of power quality. These facts devices are classified based on their construction and connection to the line i.e. called as series and shunt converters. This paper also concentrate on the concept of fuzzy logic controller for getting better performance as compared with the previous conventional controllers. Basically, the fuzzy controller has the advantage of low steady state error and also it reduces the These experimental diagrams are verified in Matlab/Simulink and the results are verified for both PI and Fuzzy controllers.

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2015 2015


Reset
Filter By Issues
All Issue Vol 14, No 5: October 2025 Vol 14, No 4: August 2025 Vol 14, No 3: June 2025 Vol 14, No 2: April 2025 Vol 14, No 1: February 2025 Vol 13, No 4: December 2024 Vol 13, No 3: September 2024 Vol 13, No 2: June 2024 Vol 13, No 1: March 2024 Vol 12, No 4: December 2023 Vol 12, No 3: September 2023 Vol 12, No 2: June 2023 Vol 12, No 1: March 2023 Vol 11, No 4: December 2022 Vol 11, No 3: September 2022 Vol 11, No 2: June 2022 Vol 11, No 1: March 2022 Vol 10, No 4: December 2021 Vol 10, No 3: September 2021 Vol 10, No 2: June 2021 Vol 10, No 1: March 2021 Vol 9, No 4: December 2020 Vol 9, No 3: September 2020 Vol 9, No 2: June 2020 Vol 9, No 1: March 2020 Vol 8, No 4: December 2019 Vol 8, No 3: September 2019 Vol 8, No 2: June 2019 Vol 8, No 1: March 2019 Vol 7, No 4: December 2018 Vol 7, No 3: September 2018 Vol 7, No 2: June 2018 Vol 7, No 1: March 2018 Vol 6, No 4: December 2017 Vol 6, No 3: September 2017 Vol 6, No 2: June 2017 Vol 6, No 1: March 2017 Vol 5, No 4: December 2016 Vol 5, No 3: September 2016 Vol 5, No 2: June 2016 Vol 5, No 1: March 2016 Vol 4, No 4: December 2015 Vol 4, No 3: September 2015 Vol 4, No 2: June 2015 Vol 4, No 1: March 2015 Vol 3, No 4: December 2014 Vol 3, No 3: September 2014 Vol 3, No 2: June 2014 Vol 3, No 1: March 2014 Vol 2, No 4: December 2013 Vol 2, No 3: September 2013 Vol 2, No 2: June 2013 Vol 2, No 1: March 2013 Vol 1, No 4: December 2012 Vol 1, No 3: September 2012 Vol 1, No 2: June 2012 Vol 1, No 1: March 2012 More Issue