Research Papers - Department of Electrical and Electronic Engineering

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Start date: 2010Subject: search.filters.subject.Comparison

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    Performance Comparison of Sea Fish Species Classification using Hybrid and Supervised Machine Learning Algorithms
    (IEEE, 2022-10-04) Nalmi, R; Rathnayake, N; Mampitiya, L.I
    In the domain of autonomous underwater vehicles, the classification of objects underwater is critical. The hazy effect of the medium causes this obstacle, and these effects are directed by the dissolved particles that lead to the reflecting and scattering of light during the formation process of the image. This paper mainly focuses on exploring the best possible image classifier for the underwater images of the different fish species. The classifications were carried out by different hybrid and supervised machine learning algorithms such as Support Vector Machine (SVM), Random Forest (RF), Neural Networks (NN), Logistic Regression (LR), Decision Tree (DT), and Naive Bayes (NB). This study compares the algorithms’ accuracy and time and analyzes crucial features to decide the most optimal algorithm. Furthermore, the results of this paper depict that using dimension reduction methods such as PCA and LDA increases the accuracy of some algorithms. Random Forest was able to outperforms with a higher accuracy of 99.89% with the proposed feature extraction methods.
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    A Comparison of Fuzzy Logic Controller and PID Controller for Differential Drive Wall-Following Mobile Robot
    (IEEE, 2019-12-18) Ratnayake, R. M. N. B; De Silva, S; Rodrigo, C. J
    This paper presents a comparison between PID controller and Fuzzy rule based controller of a differentially steered wall following mobile robot. Four different maps, generated using Mapper3 software are used to simulate the robot in MobileSim platform. The code was implemented using C++ language in ARIA development package. The robot simulation is performed with Pioneer P3-DX robot. In this study, the data was collected for each cases such as: left wall following and right wall following. In order to validate the results, maximum of 40 runs were conducted for each map and the results were compared with the illustrated methods.
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    A comparison of fuzzy logic controller and pid controller for differential drive wall-following mobile robot
    (IEEE, 2019-12-18) Ratnayake, R. M. N. B; De Silva, T. S; Rodrigo, C. J
    This paper presents a comparison between PID controller and Fuzzy rule based controller of a differentially steered wall following mobile robot. Four different maps, generated using Mapper3 software are used to simulate the robot in MobileSim platform. The code was implemented using C++ language in ARIA development package. The robot simulation is performed with Pioneer P3-DX robot. In this study, the data was collected for each cases such as: left wall following and right wall following. In order to validate the results, maximum of 40 runs were conducted for each map and the results were compared with the illustrated methods.