A novel hybrid grey wolf optimizer algorithm for unmanned aerial vehicle (UAV) path planning
C Qu, W Gai, J Zhang, M Zhong - Knowledge-Based Systems, 2020 - Elsevier
Unmanned aerial vehicle (UAV) path planning problem is an important component of UAV
mission planning system, which needs to obtain optimal route in the complicated field. To …
mission planning system, which needs to obtain optimal route in the complicated field. To …
[HTML][HTML] Improving K-means clustering with enhanced Firefly Algorithms
In this research, we propose two variants of the Firefly Algorithm (FA), namely inward
intensified exploration FA (IIEFA) and compound intensified exploration FA (CIEFA), for …
intensified exploration FA (IIEFA) and compound intensified exploration FA (CIEFA), for …
A hybrid algorithm based on state-adaptive slime mold model and fractional-order ant system for the travelling salesman problem
The ant colony optimization (ACO) is one efficient approach for solving the travelling
salesman problem (TSP). Here, we propose a hybrid algorithm based on state-adaptive …
salesman problem (TSP). Here, we propose a hybrid algorithm based on state-adaptive …
Prediction of stock market index based on ISSA-BP neural network
X Liu, J Guo, H Wang, F Zhang - Expert Systems with Applications, 2022 - Elsevier
Stock market index forecasting is a very tempting topic. Appropriate analysis of such a topic
will provide valuable insights for investors, traders and policymakers in the appealing stock …
will provide valuable insights for investors, traders and policymakers in the appealing stock …
Cooperative path planning optimization for multiple UAVs with communication constraints
L Xu, X Cao, W Du, Y Li - Knowledge-Based Systems, 2023 - Elsevier
Path planning is a complicated optimization problem that is crucial for the safe flight of
unmanned aerial vehicles (UAVs). Especially in the scenarios involving multiple UAVs, this …
unmanned aerial vehicles (UAVs). Especially in the scenarios involving multiple UAVs, this …
Hybrid algorithms based on combining reinforcement learning and metaheuristic methods to solve global optimization problems
A Seyyedabbasi, R Aliyev, F Kiani, MU Gulle… - Knowledge-Based …, 2021 - Elsevier
This paper introduces three hybrid algorithms that help in solving global optimization
problems using reinforcement learning along with metaheuristic methods. Using the …
problems using reinforcement learning along with metaheuristic methods. Using the …
Intelligent skin cancer diagnosis using improved particle swarm optimization and deep learning models
In this research, we propose an intelligent decision support system for skin cancer detection.
Since generating an effective lesion representation is a vital step to ensure the success of …
Since generating an effective lesion representation is a vital step to ensure the success of …
Intelligent driver monitoring system: An Internet of Things-based system for tracking and identifying the driving behavior
K Mohammed, M Abdelhafid, K Kamal, N Ismail… - Computer Standards & …, 2023 - Elsevier
One of the most prevalent causes of road accidents is aggressive and irrational driving,
which puts lives and property in danger. To reduce traffic crashes and improve road safety …
which puts lives and property in danger. To reduce traffic crashes and improve road safety …
Evolving ensemble models for image segmentation using enhanced particle swarm optimization
In this paper, we propose particle swarm optimization (PSO)-enhanced ensemble deep
neural networks and hybrid clustering models for skin lesion segmentation. A PSO variant is …
neural networks and hybrid clustering models for skin lesion segmentation. A PSO variant is …
Adaptive melanoma diagnosis using evolving clustering, ensemble and deep neural networks
In this research, we propose a variant of the Particle Swarm Optimization (PSO) algorithm,
namely hybrid learning PSO (HLPSO), for skin lesion segmentation and classification …
namely hybrid learning PSO (HLPSO), for skin lesion segmentation and classification …