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IAES International Journal of Artificial Intelligence (IJ-AI)

IJAI
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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 1,722 Documents

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Intelligent credit scoring system using knowledge management Bazzi Mehdi; Chamlal Hasna; El Kharroubi Ahmed; Ouaderhman Tayeb
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Promoting entrepreneurship among Moroccan young people has been challenged by a plethora of economic and social problems in the aftermath of the Arab Spring. Several government programs have been set up for young entrepreneurs. Thus, faced with the large number of credit applications solicited by these young entrepreneurs, banks resorted to artificial intelligence techniques. In this respect, this article aims at proposing a decision-making system enabling the bank to automate its credit granting process. It is a tool that allows the bank, in the first instance, to select promising projects through a scoring approach adapted to this segment of entrepreneurs. In the second step, the tool allows the setting of the maximum credit amount to be allocated to the selected project. Finally, based on the knowledge of the bank’s experts, the tool proposes a breakdown of the amount granted by the bank into several products adapted to the needs of the entrepreneur.

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

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 deep learning based technique for plagiarism detection: a comparative study Hambi El Mostafa; Faouzia Benabbou
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

The ease of access to the various resources on the web-enabled the democratization of access to information but at the same time allowed the appearance of enormous plagiarism problems. Many techniques of plagiarism were identified in the literature, but the plagiarism of idea steels the foremost troublesome to detect, because it uses different text manipulation at the same time. Indeed, a few strategies have been proposed to perform semantic plagiarism detection, but they are still numerous challenges to overcome. Unlike the existing states of the art, the purpose of this study is to give an overview of different propositions for plagiarism detection based on the deep learning algorithms. The main goal of these approaches is to provide a high quality of worlds or sentences vector representation. In this paper, we propose a comparative study based on a set of criterions like: Vector representation method, Level Treatment, Similarity Method and Dataset. One result of this study is that most of researches are based on world granularity and use the word2vec method for word vector representation, which sometimes is not suitable to keep the meaning of the whole sentences. Each technique has strengths and weaknesses; however, none is quite mature for semantic plagiarism detection.

Narx Based Short Term Wind Power Forecasting Model M. NANDANA JYOTHI; V. DINAKAR; N. S S RAVI TEJA
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 4: December 2015
Publisher : Institute of Advanced Engineering and Science

This paper contributes a short-term wind power forecasting through Artificial Neural Network with nonlinear autoregressive exogenous inputs (NARX) model. The meteorological parameters like wind speed, temperature, pressure, and air density are considered as input parameters collected from KL University area and the calculated generated power as output parameters of neural network to predict the wind power generation. Based on hybrid forecasting technique a code is developed in MATLAB at different hidden layers and delay times.

Is Parameters Quantification in Genetic Algorithm Important, How to do it? Hari Mohan Pandey
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 6, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

The term “appropriate parameters” signifies the correct choice of values has considerable effect on the performance that directs the search process towards the global optima. The performance typically is measured considering both quality of the results obtained and time requires in finding them. A genetic algorithm is a search and optimization technique, whose performance largely depends on various factors – if not tuned appropriately, difficult to get global optima. This paper describes the applicability of orthogonal array and Taguchi approach in tuning the genetic algorithm parameters. The domain of inquiry is grammatical inference has a wide range of applications. The optimal conditions were obtained corresponding to performance and the quality of results with reduced cost and variability. The primary objective of conducting this study is to identify the appropriate parameter setting by which overall performance and quality of results can be enhanced. In addition, a systematic discussion presented will be helpful for researchers in conducting parameters quantification for other algorithms.

Hybrid Genetic Algorithms for Solving Winner Determination Problem in Combinatorial Double Auction in Grid Farhad Gorbanzadeh; Ali Asghar Pourhaji Kazem
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 1, No 2: June 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (298.655 KB)

Nowadays, since grid has been turned to commercialization, using economic methods such as auction methods are appropriate for resource allocation because of their decentralized nature. Combinatorial double auction has emerged as a major model in the economy and is a good approach for resource allocation in which participants of grid, give their requests once to the combination of resources instead of giving them to different resources multiple times. One problem with the combinatorial double auction is the efficient allocation of resources to derive the maximum benefit. This problem is known as winner determination problem (WDP) and is an NP-hard problem. So far, many methods have been proposed to solve this problem and genetic algorithm is one of the best ones. In this paper, two types of hybrid genetic algorithms were presented to improve the efficiency of genetic algorithm for solving the winner determination problem. The results showed that the proposed algorithms had good efficiency and led to better answers. DOI: http://dx.doi.org/10.11591/ij-ai.v1i2.443

Age Constraints Effectiveness on the Human Community Based Genetic Algorithm (HCBGA) Nagham A. Al-Madi; Amnah A. El-Obaid
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

In this paper, we use under-age constraints and apply it to the Traveling Salesman Problem (TSP). Values and results concerning the averages and best fits of both, the Simple Standard Genetic Algorithm (SGA), and an improved approach of Genetic Algorithms named Human Community Based Genetic Algorithm (HCBGA) are being compared. Results from the TSP test on Human Community Based Genetic Algorithm (HCBGA) are presented. Best fit solutions towards slowing the convergence of solutions in different populations of different generations show better results in the Human Community Based Genetic Algorithm (HCBGA) than the Simple Standard Genetic Algorithm (SGA).

Support Vector Machines Regression for MIMO-OFDM Channel Estimation Anis Charrada
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 1, No 4: December 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.255 KB)

In this paper, we propose a robust highly selective nonlinear channel estimator for Multiple -Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) system using complex Support Vector Machines Regression (SVR) and applied to Long Term Evolution (LTE) downlink under high mobility conditions .The new method uses the information provided by the pilot signals to estimate the total frequency response of the channel in two phases: learning phase and estimation phase. The estimation algorithm makes use of the reference signals to estimate the total frequency response of the highly selective multipath channel in the presence of non-Gaussian impulse noise interfering with pilot signals. Thus, the algorithm maps trained data into a high dimensional feature space and uses the Structural Risk Minimization (SRM) principle to carry out the regression estimation for the frequency response function of the highly selective channel. The simulations show the effectiveness of the proposed method which has good performance and high precision to track the variations of the fading channels compared to the conventional LS method and it is robust under high mobility conditions.DOI: http://dx.doi.org/10.11591/ij-ai.v1i4.1832

M-ITRS: Mathematical Model for Identification of Tandem Repeats in DNA Sequence Ajay Kumar; Sunita Garhwal
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

In DNA, tandem repeat consists of two or more contiguous copies of a pattern of nucleotides. Tandem repeats of the motif are useful in many applications like molecular biology (related to genetic information of inherited diseases), forensic medicines, DNA fingerprinting and molecular markers for cancer. Various researchers designed formal models and grammars to identify two contiguous copies of the pattern. Tree-adjoining grammar cannot be designed for k-copy language. There is a need to design a formal model which will work for more than two contiguous copies of the pattern. In this paper, we have designed deep pushdown automata for k-continuous copies of the pattern for . The proposed formal model will also identify the tandem repeats without specifying the pattern and its size.

Text Wrapping Approach to natural Language Information retrieval using significant Indicator Toyin Enikuomehin; J S Sadiku
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 2, No 3: September 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (226.656 KB)

This paper continues the advancement of models proposed for Information Retrieval by understanding that, the Information Retrieval task continues to draw attention as the information repositories increase. Knowing that Natural Language presentation of user’s information need help to reduce the complexity of the search process, we propose the use of a well defined Significant Indicator, which uses the relevance index of terms derived from the position of the text, to perform retrieval. This is achieved by initiating a text wrapping process such that document representation in space could algebraically be measured and assigned appropriate function as similarity ratio for Query and Document. Benchmark tools for Information Retrieval were followed and experiment performed using TREC classified data implemented with TRECEVAL shows better performance against some baseline models. The paper suggests further research in the direction of the Significant Indicator as a method for large search space reductionDOI: http://dx.doi.org/10.11591/ij-ai.v2i3.2202

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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

Abstract

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Abstract

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Abstract

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

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

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