SYAIRILLAH, SYAIRILLAH and Oklilas, Ahmad Fali (2023) PENENTUAN JALUR TERBAIK PADA SMART TRANSPORTATION DALAM SMART CITY MENGGUNAKAN METODE ONE DIMENSIONAL CONVOLUTIONAL NEURAL NETWORK YANG DIOPTIMASI DENGAN BAYESIAN OPTIMIZATION (1DCNN-BO). Undergraduate thesis, Sriwijaya University.
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Abstract
The system for determining the best path is included in the concept of Smart Transportation where the city that applies the concept is called a Smart City. This study uses the You Only Look Once version 8 (YOLOv8) algorithm to calculate the number of vehicles based on CCTV footage, One Dimensional Convolutional Neural Network optimized with Bayesian Optimization (1DCNN-BO) to predict road density conditions based on reference tables and the A-Star algorithm. to determine the best path. The dataset used is a dataset of vehicle images totaling 4224 images and a reference table of 5 columns and 320 rows of road conditions in .csv form. YOLOv8 produces a model with a mAP of 85.4% and a test accuracy of 78.61%. Then 1DCNN produces a model accuracy of 93.75% and 100% prediction accuracy. Followed by optimizing the 1DCNN model using Bayesian Optimization resulting in a model accuracy of 96.88%, an increase of 3.13% and the prediction results are maintained at 100%. And finally the A-Star algorithm to determine the best path with the parameters of road conditions and distance traveled gets the results of line 4 as the smallest weight in all conditions, namely morning at 08.00 am and 09.00 am, noon at 01.00 pm and 02.00 pm, afternoon at 04.00 pm and 05.00 pm.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | A-Star, Bayesian Optimization, One Dimensional Convolutional Neural Network, Penentuan Jalur Terbaik, Smart City, Smart Transportation, You Only Look Once version 8. |
Subjects: | Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning T Technology > T Technology (General) > T1-995 Technology (General) |
Divisions: | 09-Faculty of Computer Science > 56201-Computer Systems (S1) |
Depositing User: | Syairillah Syairillah |
Date Deposited: | 25 Jul 2023 08:30 |
Last Modified: | 25 Jul 2023 08:30 |
URI: | http://repository.unsri.ac.id/id/eprint/121424 |
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