Vector Quantization to Visualize the Detection Process

Suzuki, Kaiyu; Matsuzawa, Tomofumi; Takimoto, Munehiro; Kambayashi, Yahiko

doi:10.5220/0010426005530561

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2022

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“…The ACO or PSO algorithm in this study is an algorithm that forms a route based on evacuee information. Since we have been studying the use of deep learning to determine the danger of a location based on camera images from unmanned vehicles such as drones [9], we would like to investigate methods for forming evacuation routes based on information from unmanned vehicles such as drones and balloons in the future.…”

Section: Additional Experimentsmentioning

confidence: 99%

Evaluation of PSO Algorithm Considering Obstacle Avoidance in Evacuation Guidance

Matsuzawa

ISHİİ

2022

Advances in the Theory of Nonlinear Analysis and Its Application

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In recent years, IoT has been expected to provide support during natural disasters, and studies focusing on ant colony optimization (ACO) have been conducted for providing evacuation routes for evacuees. We previously proposed a modied algorithm for ACO that improved on the slow convergence of ACO, but the problem with ACO-based evacuation is the time it takes the evacuees to reach a safe zone.In this study, we proposed a route suggestion algorithm that improves particle swarm optimization (PSO) to reduce the time required for ACO evacuation, and compared the performance of ACO and the proposed PSO. We also proposed a method that combines ACO and PSO and evaluated its performance.

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Section: Additional Experimentsmentioning

confidence: 99%