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29,939 Article Results

Metaheuristic optimization in neural network model for seasonal data

10.12928/telkomnika.v19i6.20409
Budi; Diponegoro University Warsito , Rukun; Diponegoro University Santoso , Hasbi; Diponegoro University Yasin
The use of metaheuristic optimization techniques in obtaining the optimal weights of neural network model for the time series was the main part of this research. The three optimization methods used as experiments were genetic algorithm (GA), particle swarm optimization (PSO), and modified bee colony (MBC). Feed forward neural network (FFNN) was the neural network (NN) architecture chosen in this research. The limitations and weaknesses of gradient-based methods for learning algorithm inspired some researchers to use other techniques. A reasonable choice is non-gradient based method. Neural network is inspired by the characteristics of creatures. Therefore, the optimization techniques which are also resemble the patterns of life in nature will be appropriate. In this study, various scenarios on the three metaheuristic optimization methods were applied to get the best one. The proposed procedure was applied to the rainfall data. The experimental study showed that GA and PSO were recommended as optimization methods at FFNN model for the rainfall data.
Volume: 19
Issue: 6
Page: 1892-1901
Publish at: 2021-12-01

Comparison of color-based feature extraction methods in banana leaf diseases classification using SVM and K-NN

10.11591/ijeecs.v24.i3.pp1523-1533
Nur Sholehah Mat Said , Hizmawati Madzin , Siti Khadijah Ali , Ng Seng Beng
In Malaysia, banana is a top fruit production which contribute to the economy growth in agriculture field. Hence, it is significant to have a quality production of banana and important to detect the plant diseases at the early stage. There are many types of banana leaf diseases such as Banana Mosaic, Black Sigatoka and Yellow Sigatoka. These three diseases are related to color changes at banana. This research paper is an experiment based and need to identify the best color feature extraction method to classify banana leaf diseases. Total of 48 banana leaf images that are used in this research paper. Four types of color feature extraction methods which are color histogram, color moment, hue, saturation, and value (HSV) histogram and color auto correlogram are experimented to determine the best method for banana leaf diseases classification. While for the classifiers, support vector machine (SVM) and k-Nearest neighbors (k-NN) are used to evaluate the performance and accuracy of each color feature extraction methods. There are also preliminary experiments to identify accurate parameters to use during classification for both classifiers. Our experimental result express that HSV histogram is the best method to classify banana leaf diseases with 83.33% of accuracy and SVM classifier perform better compared to k-NN.
Volume: 24
Issue: 3
Page: 1523-1533
Publish at: 2021-12-01

Power system operation considering detailed modelling of the natural gas supply network

10.11591/ijece.v11i6.pp4740-4750
Ricardo Moreno , Diego Larrahondo , Oscar Florez
The energy transition from fossil-fuel generators to renewable energies represents a paramount challenge. This is mainly due to the uncertainty and unpredictability associated with renewable resources. A greater flexibility is requested for power system operation to fulfill demand requirements considering security and economic restrictions. In particular, the use of gas-fired generators has increased to enhance system flexibility in response to the integration of renewable energy sources. This paper provides a comprehensive formulation for modeling a natural gas supply network to provide gas for thermal generators, considering the use of wind power sources for the operation of the electrical system over a 24-hour period. The results indicate the requirements of gas with different wind power level of integration. The model is evaluated on a network of 20 NG nodes and on a 24-bus IEEE RTS system with various operative settings during a 24-hour period.
Volume: 11
Issue: 6
Page: 4740-4750
Publish at: 2021-12-01

A novel method for determining fixed running time in operating electric train tracking optimal speed profile

10.11591/ijece.v11i6.pp4881-4890
An Thi Hoai Thu Anh , Nguyen Van Quyen
Tracking the optimal speed profile in electric train operation has been proposed as a potential solution for reducing energy consumption in electric train operation, at no cost to improve infrastructure of existing Metro lines as well. However, the optimal speed profile needs to meet fixed running time. Therefore, this paper focuses on a new method for determining the fixed running time complied with the scheduled timetable when trains track the optimal speed profile. The novel method to ensure the fixed running time is the numerical-analytical one. Calculating accelerating time ta, coasting time tc, braking time tb via values of holding speed vh, braking speed vb of optimal speed profile with the constraint condition: the running time equal to the demand time. The other hands, vh and vb are determined by solving nonlinear equations with constraint conditions. Additionally, changing running time suit for each operation stage of metro lines or lines starting to conduct schedules by the numerical-analytical method is quite easy. Simulation results obtained for two scenarios with data collected from electrified trains of Cat Linh-Ha Dong metro line, Vietnam show that running time complied with scheduled timetables, energy saving by tracking optimal speed profile for the entire route is up to 8.7%, if the running time is one second longer than original time, energy saving is about 11.96%.
Volume: 11
Issue: 6
Page: 4881-4890
Publish at: 2021-12-01

The knowledge level of dental students on color stability composite resin restoration in the COVID-19 pandemic era

10.11591/ijphs.v10i4.21038
Chaterina Anjelia , Octarina Octarina
During the COVID-19 pandemic in Indonesia, all professional program students learning online and still expected to have good knowledge including dental materials. Color stability of anterior teeth restoration is the most important thing. Professional program students with a good level of knowledge were expected to support the use of composite resin towards patients without causing discoloration. The aim of this study was to assess the knowledge level of professional program students towards color stability of composite resin restoration in the Faculty of Dentistry, Universitas Trisakti in the COVID-19 pandemic era. This was a descriptive observational study using a cross-sectional approach. Data were collected using Google Form with a questionnaire that had been tested for validity and reliability. The sample was 100 professional program students who met the inclusion criteria and accepted informed consent. This study found that in the COVID-19 pandemic era, the knowledge level of 49 respondents (49%) was good, 37 respondents (37%) were fairly good and 14 respondents (14%) were less good. The majority of the professional program students of the Faculty of Dentistry, Universitas Trisakti were in the good category of knowledge about the color stability of composite resin restoration.
Volume: 10
Issue: 4
Page: 751-757
Publish at: 2021-12-01

Numerical approach of riemann-liouville fractional derivative operator

10.11591/ijece.v11i6.pp5367-5378
Ramzi B. Albadarneh , Iqbal M. Batiha , Ahmad Adwai , Nedal Tahat , A. K. Alomari
This article introduces some new straightforward and yet powerful formulas in the form of series solutions together with their residual errors for approximating the Riemann-Liouville fractional derivative operator. These formulas are derived by utilizing some of forthright computations, and by utilizing the so-called weighted mean value theorem (WMVT). Undoubtedly, such formulas will be extremely useful in establishing new approaches for several solutions of both linear and nonlinear fractionalorder differential equations. This assertion is confirmed by addressing several linear and nonlinear problems that illustrate the effectiveness and the practicability of the gained findings.
Volume: 11
Issue: 6
Page: 5367-5378
Publish at: 2021-12-01

Overview of microgrid systems

10.11591/ijaas.v10.i4.pp378-391
V. Saravanan , K. M. Venkatachalam , M. Arumugam , M. A. K. Borelessa , K. T. M. U. Hemapala
This research paper discusses the different types of microgrids, their structural arrangements and the technology adopted for different power management projects. It also deals with various control strategies and security plans used for optimal performance. A detailed overview of the direct current (DC) microgrid system is discussed, outlining its configurations and technical-economic aspects. Performance evaluation of microgrid carried out through various reliability codes is also provided.
Volume: 10
Issue: 4
Page: 378-391
Publish at: 2021-12-01

Analysis of WEKA data mining algorithms Bayes net, random forest, MLP and SMO for heart disease prediction system: A case study in Iraq

10.11591/ijece.v11i6.pp5229-5239
Rana Riad K. AL-Taie , Basma Jumaa Saleh , Ahmed Yousif Falih Saedi , Lamees Abdalhasan Salman
Data mining is defined as a search through large amounts of data for valuable information. The association rules, grouping, clustering, prediction, sequence modeling is some essential and most general strategies for data extraction. The processing of data plays a major role in the healthcare industry's disease detection. A variety of disease evaluations should be required to diagnose the patient. However, using data mining strategies, the number of examinations should be decreased. This decreased examination plays a crucial role in terms of time and results. Heart disease is a death-provoking disorder. In this recent instance, health issues are immense because of the availability of health issues and the grouping of various situations. Today, secret information is important in the healthcare industry to make decisions. For the prediction of cardiovascular problems, (Weka 3.8.3) tools for this analysis are used for the prediction of data extraction algorithms like sequential minimal optimization (SMO), multilayer perceptron (MLP), random forest and Bayes net. The data collected combine the prediction accuracy results, the receiver operating characteristic (ROC) curve, and the PRC value. The performance of Bayes net (94.5%) and random forest (94%) technologies indicates optimum performance rather than the sequential minimal optimization (SMO) and multilayer perceptron (MLP) methods.
Volume: 11
Issue: 6
Page: 5229-5239
Publish at: 2021-12-01

Evaluation of exponential moving average application to smooth the power output of wind turbine with different control modes

10.11591/ijece.v11i6.pp4708-4717
Dinh Chung Phan , Ngọc An Luu
This paper focused on evaluating the application of exponential moving average method into wind turbine to smooth its power output without an energy storage system or an anemometer. Wind turbine control modes including active power control mode and rotor speed control mode are considered. For each control mode, two positions of the Exponential Moving Average method in controller were compared to choose the best position. Additionally, the impact of smoothing factor on wind turbine performance was also considered to determine a reasonable value of the smoothing factor for each control mode. Simulation results in MATLAB/Simulink indicated that, for wind turbine using rotor speed control mode, the Exponential Moving Average method should be applied to reduce the variation of actual rotor speed signal while for wind turbine with the power control mode, it should be used to smooth reference power signal. From the performance of wind turbine with different smoothing factor values, we can suggest that the smoothing factor value should be set at 0.5 and 0.4 for the power control mode and the rotor speed control mode, respectively.
Volume: 11
Issue: 6
Page: 4708-4717
Publish at: 2021-12-01

Distant temperature and humidity monitoring: prediction and measurement

10.11591/ijeecs.v24.i3.pp1405-1413
Farrukh Hafeez , Usman Ullah Sheikh , Attaullah Khidrani , Muhammad Akram Bhayo , Saleh Masoud Abdallah Altbawi , Touqeer Ahmed Jumani
Sensing environmental measuring parameters has a pivotal role in our everyday lives. Most of our daily life activities depend upon environmental conditions. Accurate information about these parameters also helps in several industrial applications like ventilation rate calculation, energy prediction, stock maintenance in warehouses, and saving from harmful conditions. The emergence of machine learning can make it easy to predict such time series problems. This paper describes the design of a remotely controlled robotic car for measuring and predicting humidity and temperature. A customized app for accessing the robotic car is designed to indicate predicted and realtime measured values of humidity and temperature. A sensor installed builtin helps in the measurement. The recurrent neural network (RNN) model is used to predict humidity and temperature. For this purpose, experiments are carried out in both outdoor and indoor settings. Accuracy of 85% and 90% is achieved in an outdoor environment and indoor settings.
Volume: 24
Issue: 3
Page: 1405-1413
Publish at: 2021-12-01

A performance evaluation of convolutional neural network architecture for classification of rice leaf disease

10.11591/ijai.v10.i4.pp1069-1078
Afis Julianto , Andi Sunyoto
Plant disease is a challenge in the agricultural sector, especially for rice production. Identifying diseases in rice leaves is the first step to wipe out and treat diseases to reduce crop failure. With the rapid development of the convolutional neural network (CNN), rice leaf disease can be recognized well without the help of an expert. In this research, the performance evaluation of CNN architecture will be carried out to analyze the classification of rice leaf disease images by classifying 5932 image data which are divided into 4 disease classes. The comparison of training data, validation, and testing are 60:20:20. Adam optimization with a learning rate of 0.0009 and softmax activation was used in this study. From the experimental results, the InceptionV3 and InceptionResnetV2 architectures got the best accuracy, namely 100%, ResNet50 and DenseNet201 got 99.83%, MobileNet 99.33%, and EfficientNetB3 90.14% accuracy.
Volume: 10
Issue: 4
Page: 1069-1078
Publish at: 2021-12-01

Design of vehicle using Ackermann steering with IoT concept

10.11591/ijeecs.v24.i3.pp1432-1436
Albert Paul Arunkumar , Palanisamy R. , Selvakumar K. , Usha S. , Thamizh Thentral T. M. , Karthikeyan D.
Electric vehicles are becoming more demanding these days. In this project the possibility of using Ackerman steering with electric drive servomotor is explained. Scalability is the advantage of using this mechanism which can be adopted for four-wheel vehicle system as well. The objective of this project is to do design a system using Ackerman steering which determines the maximum and minimum angle of the turning of the wheels. It also avoids the front tire slippage and activates pure rolling. Ackermann steering geometry is a geometric arrangement of linkages in the steering of a car or other vehicle designed to solve the problem of wheels on the inside and outside of a turn needing to trace out circles of different radii. The geometrical solution to this is for all wheels to have their axles arranged as radii of circles with a common centre point. As the rear wheels are fixed, this centre point must be on a line extended from the rear axle. Intersecting the axes of the front wheels on this line as well requires that the inside front wheel be turned, when steering, through a greater angle than the outside wheel. The microcontroller used in this project is ATMega16 andlmax232 is used for the serial data transmission.
Volume: 24
Issue: 3
Page: 1432-1436
Publish at: 2021-12-01

Knowledge, attitude, and practice towards COVID-19 among university students in Indonesia: A cross-sectional study

10.11591/ijphs.v10i4.21012
Sulistyawati Sulistyawati , Syamsu Hidayat , Siwi Pramatama Mars Wijayanti , Tri Wahyuni Sukesi , Siti Kurnia Widi Hastuti , Surahma Asti Mulasari , Fatwa Tentama , Rokhmayanti Rokhmayanti , Ulinnuha Yudiansa Putra , Sitti Nur Djannah
The presence of asymptomatic people exacerbates the widespread Coronavirus disease (COVID-19) transmission. The majority of them come from young people. This study aimed to explore the knowledge, attitude, and practice related to COVID-19 among university students in Indonesia, and the potential factor influenced their knowledge. A cross-sectional study involved 1,427 university students were carried out using an online survey from March 28 to April 10, 2020. A structured questionnaire consist of six sections focuses on knowledge, attitude, and preventive measure related to COVID-19 was used to collect the data. The analysis was performed using descriptive, Mann-Whitney, and Kruskal-Wallis tests. Results of the analysis indicated a significant difference in terms of mean between males and females regarding knowledge about preventing and protect others from COVID-19, the risk factor of getting COVID-19 infection, and knowledge that COVID-19 is curable. Knowledge total score among the respondent, there was a significant difference within the research group. This study demonstrates that the respondent has a basic knowledge about COVID-19 and the proper attitude, but it seems they are not consistent on practice in a particular measure.
Volume: 10
Issue: 4
Page: 735-743
Publish at: 2021-12-01

Factors of academic stress: Do they impact English academic performance?

10.11591/ijere.v10i4.21296
Erlinda D. Tibus , Sybill Krizzia G. Ledesma
This study investigated the college students’ level of academic performance and determined the impact of academic stress on their English academic performance. This employed a descriptive-exploratory research design with Exploratory Factor Analysis (EFA) and correlation analysis (Pearson r) as main analyses using statistical software. The result suggested that the students (N=250) have a moderate level of stress. Likewise, seven factors were generated through EFA but were reduced to four factors using parallel analysis, the factors are perceived personal stress, classroom stress, performance stress, and time management stress. In the correlation analysis, it was found out that perceived personal stress, classroom stress, and performance stress are significantly correlated except for time management stress. Moreover, these factors were found to have no significant relationship with the English grades of the students. With this result, it is concluded that despite having a moderate level of academic stress, students were able to manage them by using a plethora of coping mechanisms available. The institutions should offer prevention and intervention services that directly address the academic stress of the students to ensure academic success.
Volume: 10
Issue: 4
Page: 1446-1454
Publish at: 2021-12-01

Differential equations of motion of a material point in the perpendicular plane to the plane of the gravitating disk

10.11591/ijeecs.v24.i3.pp1307-1314
Zhenisgul Rakhmetullina , Indira Uvaliyeva , Farida Amenova
This paper presents an analytical solution of the differential equations of motion of a material point in the plane perpendicular to the plane of the gravitating disk. The differential equations of the problem under study and the applied Gilden's method are described in the works of A. Poincaré. Differential equations refer to nonlinear equations. The analysis of methods for solving nonlinear differential equations was carried out. The methodology of applying the Gilden method to the solution of the differential equations under consideration can be applied in studies of the problem of the motion of celestial bodies in the “disk-material point” system in perpendicular planes. To identify the various properties of the gravitating disk, an analytical review of the state of the problem of the motion of a material point in the field of a gravitating disk is carried out. Summing up the presented review on the problem under study, a conclusion is made. The substantive formulation of the problem is described, which is formulated as follows: the study of the influence of disk-shaped bodies on the motion of a material point and methods for their solution.
Volume: 24
Issue: 3
Page: 1307-1314
Publish at: 2021-12-01
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