A state-of-the-art differential evolution algorithm for parameter estimation of solar photovoltaic models
Photovoltaic (PV) generation systems are vital to the utilization of the sustainable and
pollution-free solar energy. However, the parameter estimation of PV systems remains very …
pollution-free solar energy. However, the parameter estimation of PV systems remains very …
Chaotic local search-based differential evolution algorithms for optimization
JADE is a differential evolution (DE) algorithm and has been shown to be very competitive in
comparison with other evolutionary optimization algorithms. However, it suffers from the …
comparison with other evolutionary optimization algorithms. However, it suffers from the …
A multi-layered gravitational search algorithm for function optimization and real-world problems
A gravitational search algorithm (GSA) uses gravitational force among individuals to evolve
population. Though GSA is an effective population-based algorithm, it exhibits low search …
population. Though GSA is an effective population-based algorithm, it exhibits low search …
Heuristic scheduling of batch production processes based on petri nets and iterated greedy algorithms
Wire rod and bar rolling is an important batch production process in steel production
systems. A scheduling problem originated from this process is studied in this work by …
systems. A scheduling problem originated from this process is studied in this work by …
Surrogate-assisted autoencoder-embedded evolutionary optimization algorithm to solve high-dimensional expensive problems
Surrogate-assisted evolutionary algorithms (EAs) have been intensively used to solve
computationally expensive problems with some success. However, traditional EAs are not …
computationally expensive problems with some success. However, traditional EAs are not …
Optimizing weighted extreme learning machines for imbalanced classification and application to credit card fraud detection
The classification problems with imbalanced datasets widely exist in real word. An Extreme
Learning Machine is found unsuitable for imbalanced classification problems. This work …
Learning Machine is found unsuitable for imbalanced classification problems. This work …
Competition-driven multimodal multiobjective optimization and its application to feature selection for credit card fraud detection
Feature selection has been considered as an effective method to solve imbalanced
classification problems. It can be formulated as a multiobjective optimization problem (MOP) …
classification problems. It can be formulated as a multiobjective optimization problem (MOP) …
Improving dendritic neuron model with dynamic scale-free network-based differential evolution
Some recent research reports that a dendritic neuron model (DNM) can achieve better
performance than traditional artificial neuron networks (ANNs) on classification, prediction …
performance than traditional artificial neuron networks (ANNs) on classification, prediction …
An aggregative learning gravitational search algorithm with self-adaptive gravitational constants
The gravitational search algorithm (GSA) is a meta-heuristic algorithm based on the theory
of Newtonian gravity. This algorithm uses the gravitational forces among individuals to move …
of Newtonian gravity. This algorithm uses the gravitational forces among individuals to move …
An intelligent metaphor-free spatial information sampling algorithm for balancing exploitation and exploration
In this paper, we propose an intelligent scheme and design a spatial information sampling
algorithm (SIS) to achieve a balance between exploitation and exploration more efficiently …
algorithm (SIS) to achieve a balance between exploitation and exploration more efficiently …