Multi-objective optimal short-term planning of renewable distributed generations and capacitor banks in power system considering different uncertainties including …
The increasing penetration of solar distributed generations (SDGs) and wind distributed
generations (WDGs) together with plug-in electric vehicles (PEVs) will lead to a promising …
generations (WDGs) together with plug-in electric vehicles (PEVs) will lead to a promising …
Adaptive neural network control and optimal path planning of UAV surveillance system with energy consumption prediction
RJ Wai, AS Prasetia - Ieee Access, 2019 - ieeexplore.ieee.org
A surveillance system is one of the most interesting research topics for an unmanned aerial
vehicle (UAV). However, the problem of planning an energy-efficient path for the …
vehicle (UAV). However, the problem of planning an energy-efficient path for the …
Adaptive path planning for fusing rapidly exploring random trees and deep reinforcement learning in an agriculture dynamic environment UAVs
GGR Castro, GS Berger, A Cantieri, M Teixeira, J Lima… - Agriculture, 2023 - mdpi.com
Unmanned aerial vehicles (UAV) are a suitable solution for monitoring growing cultures due
to the possibility of covering a large area and the necessity of periodic monitoring. In …
to the possibility of covering a large area and the necessity of periodic monitoring. In …
Dynamic path planning based on neural networks for aerial inspection
Abstract Unmanned Aerial Vehicles are a suitable solution to automate inspections on large
structures that require periodic monitoring once this process could be complex and highly …
structures that require periodic monitoring once this process could be complex and highly …
Modified crayfish optimization algorithm with adaptive spiral elite greedy opposition-based learning and search-hide strategy for global optimization
G Li, T Zhang, CY Tsai, Y Lu, J Yang… - … of Computational Design …, 2024 - academic.oup.com
Crayfish optimization algorithm (COA) is a novel bionic metaheuristic algorithm with high
convergence speed and solution accuracy. However, in some complex optimization …
convergence speed and solution accuracy. However, in some complex optimization …
[PDF][PDF] An investigation of digital forensics for shamoon attack behaviour in FOG computing and threat intelligence for incident response
A Almaiah, O Almomani - J. Theor. Appl. Inf. Technol, 2020 - researchgate.net
Cyber related crimes are increasing nowadays. Thus digital forensics has been employed in
solving cybercrimes. Several researches have been done where they have analysed cyber …
solving cybercrimes. Several researches have been done where they have analysed cyber …
Gaining insights into conceptual models: a graph-theoretic querying approach
Featured Application A capability to query and gain insights into complex OPM ISO 19450-
based conceptual mod-els using OPCloud by answering questions such as “what if”, cause …
based conceptual mod-els using OPCloud by answering questions such as “what if”, cause …
On the traveling salesman problem in nautical environments: an evolutionary computing approach to optimization of tourist route paths in Medulin, Croatia
Sažetak The Traveling salesman problem (TSP) defines the problem of finding the optimal
path between multiple points, connected by paths of a certain cost. This paper applies that …
path between multiple points, connected by paths of a certain cost. This paper applies that …
A twin learning framework for traveling salesman problem based on autoencoder, graph filter, and transfer learning
J Wu, H Yang, Y Zeng, Z Wu, J Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Efficient solvers for traveling salesman problem (TSP) have great significance in the field of
consumer electronic systems and devices. Existing studies require independent and …
consumer electronic systems and devices. Existing studies require independent and …
A comparative study on genetic algorithm and reinforcement learning to solve the traveling salesman problem
A Uthayasuriyan, H Chandran, UV Kavvin… - Research Reports on …, 2023 - ojs.wiserpub.com
Abstract Machine Learning (ML) and Evolutionary Computing (EC) are the two most popular
computational methodologies in computer science to solve learning and optimization …
computational methodologies in computer science to solve learning and optimization …