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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Wesam M. Jasim
University of Anbar
Computer Science & IT Electrical & Electronics Engineering Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

 1 
Hybrid metaheuristic approach for robot path planning in dynamic environment Lina Basem Amar; Wesam M. Jasim
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2836

Abstract

Recently robots have gained great attention due to their ability to operate in dynamic and complex environments with moving obstacles. The path planning of a moving robot in a dynamic environment is to find the shortest and safe possible path from the starting point towards the desired target point. A dynamic environment is a robot's environment that consists of some static and moving obstacles. Therefore, this problem can be considered as an optimization problem and thus it is solved via optimization algorithms. In this paper, three approaches for determining the optimal pathway of a robot in a dynamic environment were proposed. These approaches are; the particle swarming optimization (PSO), ant colony optimization (ACO), and hybrid PSO and ACO. These used to carry out the path planning tasks effectively. A set of certain constraints must be met simultaneously to achieve the goals; the shortest path, the least time, and free from collisions. The results are calculated for the two algorithms separately and then that of the hybrid algorithm is calculated. The effectiveness and superiority of the hybrid algorithm were verified on both PSO and ACO algorithms.
Pre-convoluted neural networks for fashion classification Mustafa Amer Obaid; Wesam M. Jasim
Bulletin of Electrical Engineering and Informatics Vol 10, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i2.2750

Abstract

In this work, concept of the fashion-MNIST images classification constructed on convolutional neural networks is discussed. Whereas, 28×28 grayscale images of 70,000 fashion products from 10 classes, with 7,000 images per category, are in the fashion-MNIST dataset. There are 60,000 images in the training set and 10,000 images in the evaluation set. The data has been initially pre-processed for resizing and reducing the noise. Then, this data is normalized for ensuring that all the data are on the same scale and this usually improves the performance. After normalizing the data, it is augmented where one image will be in three forms of output. The first output image is obtained by rotating the actual one; the second output image is obtained as acute angle image; and the third is obtained as tilt image. The new data set is of 180,000 images for training phase and 30,000 images for the testing phase. Finally, data is sent to training process as input for training model of the pre-convolution network. The pre-convolution neural network with the five layered convoluted deep neural network and do the training with the augmented data, The performance of the proposed system shows 94% accuracy where it was 93% in VGG16 and 92% in AlexNetnetworks.
Diabetics blood glucose control based on GA-FOPID technique Wesam M. Jasim; Yousif I. Al Mashhadany
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2715

Abstract

In this paper, an optimized Fractional Order Proportional, Integral, Derivative based Genetic Algorithm GA-FOPID optimization technique is proposed for glucose level normalization of diabetic patients. The insulin pump with diabetic patient system used in the simulation is the Bergman minimal model, which is used to simulate the overall system. The main purpose is to obtain the optimal controller parameters that regulate the system smoothly to the desired level using GA optimization to find the FOPID parameters. The next step is to obtain the FOPID controller parameters and the traditional PID controller parameters normally. Then, the simulation output results of using the proposed GA-FOPID controller was compared with that of using the normal FOPID and the traditional PID controllers. The comparison shows that all the three controllers can regulate the glucose level but the use of GA-FOPID controller was outperform the use of the other two controllers in terms of speed of normalization and the overshoot value.
Co-Authors Asmaa Yaseen Nawaf Baraa M. Abed Lina Basem Amar Mustafa Amer Obaid Yousif I. Al Mashhadany