0% Complete
Home
/
13th International Conference on Computer and Knowledge Engineering
The application of Brain Drain Optimization algorithm on static drone placement problem
Authors :
Mohammad Mehdi Samimi
1
Alireza Basiri
2
1- Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan, 84156-83111, Iran
2- Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan, 84156-83111, Iran
Keywords :
Static Drone Placement،Swarm Intelligence،BRADO،Optimization
Abstract :
With the advancement of technology, the desire to use more robots and computers instead of humans has also grown. One of the robots that can be used in lots of situations is a drone. Drones can be used to control or monitor some targets but finding the optimal position for them to fly is a big problem that is in the group of NP-hard problems. In this paper, we tried to solve the static drone placement problem with a recently-proposed swarm intelligence algorithm called BRADO which is derived from the migration of humans between countries. The results of our experiments show that BRADO has worked well in solving the problem. In our tests, we used static drones and targets deployed in a squared search space and our goal is to find the optimal position for the drones in a way that all of the targets will be covered. The results of our proposed solution were better than some other famous meta-heuristic algorithms. The outcome of our work shows that BRADO works well with the static drone placement problem.
Papers List
List of archived papers
An Improved and Accurate Measure for Mining Correlated High-utility Itemsets
Amir Masoud Heidari Orojloo - Morteza Keshtkaran
Capsule Routing over Stacked GCN-GAT Embeddings with Negative Sampling for Graph Link Prediction
Fatemeh Safari Sarvandi - Sayeh Mirzaei - Rooholah Abedian
Bridging Knowledge and Language Models in Healthcare: A RAG Survey
Seyedali Hasanzadeh - Fahimeh Ghasemian - Elham Shabaninia
Online Task Offloading and Scheduling in Fog-Cloud Environment based on Reinforcement Learning
Ali Sheidaee - Leili Farzinvash - Alireza Sokhandan
Multi-Task Transformer for Stock Market Trend Prediction
Seyed Morteza Mirjebreili - Ata Solouki - Hamidreza Soltanalizadeh - Mohammad Sabokrou
Zone-Based Federated Learning in Indoor Positioning
Omid Tasbaz - Vahideh Moghtadaiee - Bahar Farahani
Lightweight Local Transformer for COVID-19 Detection Using Chest CT Scans
Hojat Asgarian Dehkordi - Hossein Kashiani - Amir Abbas Hamidi Imani - Shahriar Baradaran Shokouhi
Assessing Users' Influence on Respondents in Conversation Quality: A Quantitative Study on Reddit Based on the Cooperative Principle
Afsaneh Habibi - Fattaneh Taghiyareh
Hybrid navigation based on GPS data and SIFT-based place recognition using Biologically-inspired SLAM
Sahar Salimpour Kasebi - Hadi Seyedarabi - Javad Musevi Niya
Speech Emotion Recognition Using a Hierarchical Adaptive Weighted Multi-Layer Sparse Auto-Encoder Extreme Learning Machine with New Weighting and Spectral/SpectroTemporal Gabor Filter Bank Features
Fatemeh Daneshfar - Seyed Jahanshah Kabudian
more
Samin Hamayesh - Version 44.5.0