A comprehensive survey on particle swarm optimization algorithm and its applications
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review
M Janga Reddy, D Nagesh Kumar - h2oj, 2020 - iwaponline.com
During the last three decades, the water resources engineering field has received a
tremendous increase in the development and use of meta-heuristic algorithms like …
tremendous increase in the development and use of meta-heuristic algorithms like …
A hybrid multi-objective optimization approach for energy-absorbing structures in train collisions
Energy-absorbing structure, which is the most effective and direct protection component, is
installed at the front of the head car. However, structural optimization problems of this …
installed at the front of the head car. However, structural optimization problems of this …
A comparative study of the improvement of performance using a PSO modified by ACO applied to TSP
Swarm-inspired optimization has become very popular in recent years. Particle swarm
optimization (PSO) and Ant colony optimization (ACO) algorithms have attracted the interest …
optimization (PSO) and Ant colony optimization (ACO) algorithms have attracted the interest …
Multi-objective Ant Colony Optimization
Ant colony optimization (ACO) algorithm is one of the most popular swarm-based algorithms
inspired by the behavior of an ant colony to find the shortest path for food. The multi …
inspired by the behavior of an ant colony to find the shortest path for food. The multi …
[PDF][PDF] Research on the evaluation of the resilience of subway station projects to waterlogging disasters based on the projection pursuit model
L Liu, H Wu, J Wang, T Yang - Mathematical biosciences and …, 2020 - aimspress.com
To improve sustainable development, increasingly more attention has been paid to the
evaluation of the resilience to waterlogging disasters. This paper proposed a projection …
evaluation of the resilience to waterlogging disasters. This paper proposed a projection …
Machine learning-based optimization design of bistable curved shell structures with variable thickness
The mechanical performance of curved shell structures is difficult to predict due to their
complex geometric nonlinearity. There have been many efforts to improve the mechanical …
complex geometric nonlinearity. There have been many efforts to improve the mechanical …
Novel associative classifier based on dynamic adaptive PSO: Application to determining candidates for thoracic surgery
V Mangat, R Vig - Expert Systems with Applications, 2014 - Elsevier
Association rule mining is a data mining technique for discovering useful and novel patterns
or relationships from databases. These rules are simple to infer and intuitive and can be …
or relationships from databases. These rules are simple to infer and intuitive and can be …
Genesis of basic and multi-layer echo state network recurrent autoencoders for efficient data representations
It is a widely accepted fact that data representations intervene noticeably in machine
learning tools. The more they are well defined the better the performance results are …
learning tools. The more they are well defined the better the performance results are …
A firefly colony and its fuzzy approach for server consolidation and virtual machine placement in cloud datacenters
B Perumal, A Murugaiyan - Advances in Fuzzy Systems, 2016 - Wiley Online Library
Managing cloud datacenters is the most prevailing challenging task ahead for the IT
industries. The data centers are considered to be the main source for resource provisioning …
industries. The data centers are considered to be the main source for resource provisioning …