PSO-based analysis of Echo State Network parameters for time series forecasting
Abstract Echo State Networks, ESNs, are standardly composed of additive units undergoing
sigmoid function activation. They consist of a randomly recurrent neuronal infra-structure …
sigmoid function activation. They consist of a randomly recurrent neuronal infra-structure …
Novel single and multi-layer echo-state recurrent autoencoders for representation learning
Abstract Representation learning impacts the performance of Machine Learning (ML)
models. Feature extraction-based methods such as Auto-Encoders (AEs) are used to find …
models. Feature extraction-based methods such as Auto-Encoders (AEs) are used to find …
Single-and multi-objective particle swarm optimization of reservoir structure in echo state network
Echo State Networks ESNs are specific kind of recurrent networks providing a black box
modeling of dynamic non-linear problems. Their architecture is distinguished by a randomly …
modeling of dynamic non-linear problems. Their architecture is distinguished by a randomly …
Evolving flexible beta basis function neural tree using extended genetic programming & hybrid artificial bee colony
In this paper, a new hybrid learning algorithm is introduced to evolve the flexible beta basis
function neural tree (FBBFNT). The structure is developed using the Extended Genetic …
function neural tree (FBBFNT). The structure is developed using the Extended Genetic …
Designing beta basis function neural network for optimization using artificial bee colony (abc)
This paper presents an application of swarm intelligence technique namely Artificial Bee
Colony (ABC) to design the design of the Beta Basis Function Neural Networks (BBFNN) …
Colony (ABC) to design the design of the Beta Basis Function Neural Networks (BBFNN) …
Nonlinear QSAR models with high-dimensional descriptor selection and SVR improve toxicity prediction and evaluation of phenols on Photobacterium phosphoreum
Assessment of the risk of chemicals is an important task in the environmental protection. In
this paper, we developed quantitative structure–activity relationship (QSAR) methods to …
this paper, we developed quantitative structure–activity relationship (QSAR) methods to …
PSO-based update memory for Improved Harmony Search algorithm to the evolution of FBBFNT'parameters
In this paper, a PSO-based update memory for Improved Harmony Search (PSOUM-IHS)
algorithm is proposed to learn the parameters of Flexible Beta Basis Function Neural Tree …
algorithm is proposed to learn the parameters of Flexible Beta Basis Function Neural Tree …
Computational QSAR models with high-dimensional descriptor selection improve antitumor activity design of ARC-111 analogues
ARC-111 has potent topoisomerase I-targeting activity and pronounced antitumor activity. To
design ARC-111 analogues with improved efficiency, we performed analyses on the …
design ARC-111 analogues with improved efficiency, we performed analyses on the …
[PDF][PDF] Designing Beta Basis Function Neural Network for Optimization Using Artificial Bee Colony (ABC)
A Abraham - academia.edu
This paper presents an application of swarm intelligence technique namely Artificial Bee
Colony (ABC) to design the design of the Beta Basis Function Neural Networks (BBFNN) …
Colony (ABC) to design the design of the Beta Basis Function Neural Networks (BBFNN) …