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INDONESIA
International Journal of Intelligent Systems and Applications in Engineering
Published by Ismail SARITAS
ISSN : 21476799     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal of Intelligent Systems and Applications in Engineering (IJISAE) is an international and interdisciplinary journal for both invited and contributed peer reviewed articles that intelligent systems and applications in engineering at all levels. The journal publishes a broad range of papers covering theory and practice in order to facilitate future efforts of individuals and groups involved in the field. IJISAE, a peer-reviewed double-blind refereed journal, publishes original papers featuring innovative and practical technologies related to the design and development of intelligent systems in engineering. Its coverage also includes papers on intelligent systems applications in areas such as nanotechnology, renewable energy, medicine engineering, Aeronautics and Astronautics, mechatronics, industrial manufacturing, bioengineering, agriculture, services, intelligence based automation and appliances, medical robots and robotic rehabilitations, space exploration and etc.
Arjuna Subject : -
Articles 200 Documents
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A Modified Flower Pollination Algorithm for Fractional Programming Problems metwalli, mohamed Abdel-Baset; hezam, ibrahim
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 3 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.56680

Abstract

Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, a new method is developed chaos-based Flower Pollination Algorithm (CFPA) to solve Fractional Programming Problems (FPPs). The proposed algorithm is tested using several ROP benchmarks. The test aims to prove the capability of the CFPA to solve any type of FPPs. The solution results employing the CFPA algorithm are compared with a number of exact and metaheuristic solution methods used for handling FPPs. Numerical examples are given to show the feasibility, effectiveness, and robustness of the proposed algorithm. The results obtained using CFPA indicated the superiority of the proposed technique among others in computational time.
Multi objective design optimization of plate fin heat sinks using improved differential search algorithm Turgut, Oguz Emrah
International Journal of Intelligent Systems and Applications in Engineering Vol 6, No 1 (2018)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2018637924

Abstract

This study provides the multi-objective optimization of plate fin heat sinks equipped with flow – through and impingement-flow air-cooling system by using Improved Differential Search algorithm. Differential Search algorithm mimics the subsistence characteristics of the living beings through the migration process. Convergence speed of the algorithm is enhanced with the local search based perturbation schemes and this improvement yields favorable solution outputs according to the results obtained from the widely quoted optimization test problems. Improved algorithm is employed on multi-objective design optimization of plate fins heat sink considering the objective functions of entropy generation rate and total material cost. Total of seven decision variables such as oncoming stream velocity, number of fins on the plate, gap between consecutive fins, base thickness of the plate, width, length and height of the plate fin heat sink are selected to be optimized. Pareto frontiers are constructed for both flow-through and impingement flow air-cooling system design and best solutions are obtained   by means of widely reputed decision-making theories of LINMAP, TOPSIS, and Shannon’s entropy theory. Results retrieved from the case studies show that reliable outcomes could be achieved in terms of solution accuracy through   Improved Differential Search optimizer.   
Simple and Novel Approach for Image Representation with Application to Face Recognition Eleyan, Alaa
International Journal of Intelligent Systems and Applications in Engineering Vol 5, No 3 (2017)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2017531423

Abstract

In this paper a new statistical image descriptor for the face recognition problem is proposed. To the best of our knowledge, no one has attempted to implement this approach before. The idea is simple and straight forward. For each face image, a feature descriptor is formed by concatenating 4 vectors together. These four vectors are formed by taking the sum of pixels in four different directions, namely; row-wise sum (0), column-wise sum (90 ), diagonal-wise sum (45 ) and antidiagonal-wise sum (-45 ). For test purposes, the generated feature descriptor is used in face recognition problem. The experiments are carried out on two different face databases namely; ORL and PUT databases. Simulation results show that the proposed approach gave a comparative performance to the well-known feature extraction algorithms in face recognition.
SLAM – Map Building and Navigation via ROS Pajaziti, Arbnor
International Journal of Intelligent Systems and Applications in Engineering Vol 2, No 4 (2014)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The presented work describes a ROS based control system of a Turtlebot robot for mapping and navigation in indoor environments. It presents the navigation of Turtlebot in self-created environment. The mapping process is done by using the GMapping algorithm, which is an open source algorithm and the localization process is done by using the AMCL pack. There are ROS built functions used in order to perform navigation of Turtlebot. The SLAM method implemented in ROS has proven a way for robots to do localization and mapping autonomously. The aim defined in paper to fulfill mapping, localization and navigation of Turtlebot in new and unknown environment is achieved.
Modelling and Evaluating Air Quality with Fuzzy Logic Algorithm-Ankara-Cebeci Sample Atacak, Ismail; Arici, Nursal; Guner, Dilem
International Journal of Intelligent Systems and Applications in Engineering Vol 5, No 4 (2017)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2017533902

Abstract

Air is one of the most important life sources for all living things. Gases that are present and absent in the composition of clean air also considered as pollutants in the atmosphere. If the pollutants rise above a certain concentration level, air pollution occurs. Air pollution damages all living things, especially human health. Accurate estimation of pollutant concentrations through air pollution modeling has an important effect in reducing the adverse effects of pollution and taking necessary precautions. Conventional statistical models are widely used in air pollution forecasting and modeling. As a different approach, in this study, fuzzy logic algorithm, which has been increasingly successful in many field applications, has been used to model air quality and air pollution analyzes were made based on this model. Ankara -Cebeci province data was used in the sample of the research.
Training Of Artificial Neural Network Using Metaheuristic Algorithm Alwaisi, Shaimaa Safaa Ahmed; Baykan, Omer Kaan
International Journal of Intelligent Systems and Applications in Engineering 2017: Special Issue
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2017SpecialIssue31417

Abstract

This article clarify enhancing classification accuracy of Artificial Neural Network (ANN) by using metaheuristic optimization algorithm. Classification accuracy of ANN depends on the well-designed ANN model. Well-designed ANN model Based on the structure, activation function that are utilized for ANN nodes, and the training algorithm which are used to detect the correct weight for each node. In our paper we are focused on improving the set of synaptic weights by using Shuffled Frog Leaping metaheuristic optimization algorithm which are determine the correct weight for each node in ANN model. We used 10 well known datasets from UCI machine learning repository. In order to investigate the performance of ANN model we used datasets with different properties. These datasets have categorical, numerical and mixed properties. Then we compared the classification accuracy of proposed method with the classification accuracy of back propagation training algorithm. The results showed that the proposed algorithm performed better performance in the most used datasets.
A Low Cost Single Board Computer Based Mobile Robot Motion Planning System for Indoor Environments Solak, Serdar; Dogru Bolat, Emine; Tuncer, Adem; Yildirim, Mehmet
International Journal of Intelligent Systems and Applications in Engineering Vol 4, No 4 (2016)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2016426379

Abstract

In this study, a low cost, flexible and modular structure is proposed for mobile robot motion planning systems in an indoor environment with obstacles. In this system, the mobile robot has to follow the shortest path to the target avoiding obstacles. It is designed as three main modules including image processing, path planning and robot motion blocks. These modules are embedded on a single board computer. In the image processing module, the image of the indoor environment, including a mobile robot, obstacles and a target, having different colors is taken to the single board computer with a wireless IP camera. This image is processed to find the locations of the mobile robot, obstacles and the target in C programming language using OpenCV. In path planning module, the shortest and optimal path is generated for the mobile robot. Generated path is applied to the robot motion module to produce necessary angles and distances for the mobile robot to reach the target. Since the structure of the proposed system is designed as modular and flexible, similar or different hardware, software or methods can be applied to these three modules.
The Impact of Enhanced Space Forests with Classifier Ensembles on Biomedical Dataset Classification Kilimci, Zeynep Hilal; Ilhan Omurca, Sevinc
International Journal of Intelligent Systems and Applications in Engineering Vol 6, No 2 (2018)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/Ilhan

Abstract

In this paper, we propose to improve the classification success of classifier ensembles by investigating the contribution of enhanced space forests on biomedical datasets. For this purpose, this study especially is focused on enhanced feature spaces by implementing the most popular feature selection techniques, namely information gain (IG), and chi-square (CHI). After performing these methods on the feature space, training phase is evaluated with all the original and the most significant features. That is, the new training dataset is constructed by combining the original features and the new ones. Then, the training is done with the well-known classification algorithm namely decision tree, using the enhanced feature space. Finally, three types of ensemble algorithms, namely bagging, random subspace, and random forest are carried out. A wide range of comparative experiments are conducted on publicly available and widely-used 36 datasets from the UCI machine learning repository to observe the impact of the enhanced space forests with classifier ensembles. Experiment results demonstrate that the proposed enhanced space forests perform better classification accuracy than the state of the art studies. Approximately, 1% - 3% improvement of the classification success is an indicator that our proposed technique is efficient.
A Review on Business Intelligence and Big Data Sirin, Erkan; Karacan, Hacer
International Journal of Intelligent Systems and Applications in Engineering Vol 5, No 4 (2017)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2017533861

Abstract

Improvement of data generating, processing, storing and networking technologies has made storing, capturing and sharing of data easier and cheaper than before and has enabled organizations to handle huge volume of data at high velocity and variety, named as big data. Big data offers many opportunities when the associated difficulties are addressed properly. Business Intelligence (BI) basically focuses on transforming raw data into usable, valuable and actionable information for decision-making. It can be classified as a kind of data-driven decision support system. Although big data related papers have increased for last fifteen years, there are not sufficient papers that directly overviews big data impact on BI. As data is growing exponentially, storage, process and analytics tools and technologies become more important for BI solutions. With the advent of big data, BI’s concept, architecture and capabilities are meant to be changed. Unlike a decades before, BI now is to be extract value from huge data ocean by using big data tools as well as classical ones. So, an interclusion has emerged between big data and BI. This paper overviews the current state of the art of BI and big data, and discuss how big data era affects BI solutions in general context.
Vulnerability Analysis of Multiple Critical Fault Outages and Adaptive Under Voltage Load Shedding Scenarios in Marmara Region Electrical Power Grid Pamuk, Nihat
International Journal of Intelligent Systems and Applications in Engineering Vol 5, No 1 (2017)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2017526693

Abstract

The utilization of electrical power system has been rising frequently from past to now and there is a need of dependable electrical transmission and distribution networks so as to ensure continuous and balanced energy. Besides, conventional energy governance systems have been forced to change as a result of rises in the usage of renewable energy resources and the efficiency of demand-side on the market. In this regard, electrical power systems should be planned and operated, appropriately and the balance of production and consumption demand should be provided within the nominal voltage limits. In this study, firstly, the current status of Marmara region interconnected power grid in Turkey is evaluated. Afterwards, the multiple cascading failure outages scenarios are modeled by “DIgSILENT Power Factory V14” software. The critical transmission line scenarios are implemented on the high voltage power grid model improved. These scenarios are based on the period of maximum and minimum production and consumption demand and the effects of demand response in this period. As a result of grid vulnerability analyses performed, several findings has been obtained about the impacts of different line scenarios on the high voltage transmission system, the optimization of power grid voltage profile and the role of production and consumption demand response on voltage regulation.

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