Competition and collaboration in cooperative coevolution of Elman recurrent neural networks for time-series prediction

R Chandra - IEEE transactions on neural networks and learning …, 2015 - ieeexplore.ieee.org
Collaboration enables weak species to survive in an environment where different species
compete for limited resources. Cooperative coevolution (CC) is a nature-inspired …

Financial time series prediction using hybrids of chaos theory, multi-layer perceptron and multi-objective evolutionary algorithms

V Ravi, D Pradeepkumar, K Deb - Swarm and Evolutionary Computation, 2017 - Elsevier
Abstract Financial Time Series Prediction is a complex and a challenging problem. In this
paper, we propose two 3-stage hybrid prediction models wherein Chaos theory is used to …

Evolutionary multi-objective generation of recurrent neural network ensembles for time series prediction

C Smith, Y Jin - Neurocomputing, 2014 - Elsevier
Ensembles have been shown to provide better generalization performance than single
models. However, the creation, selection and combination of individual predictors is critical …

Time series forecasting using sequence-to-sequence deep learning framework

S Du, T Li, SJ Horng - 2018 9th international symposium on …, 2018 - ieeexplore.ieee.org
Time series forecasting has been regarded as a key research problem in various fields. such
as financial forecasting, traffic flow forecasting, medical monitoring, intrusion detection …

Prediction of stock index futures prices based on fuzzy sets and multivariate fuzzy time series

BQ Sun, H Guo, HR Karimi, Y Ge, S Xiong - Neurocomputing, 2015 - Elsevier
This paper makes a prediction of Chinese stock index (CSI) future prices using fuzzy sets
and multivariate fuzzy time series method. We select Chinese CSI 300 index futures as the …

A new clinical spectrum for the assessment of nonalcoholic fatty liver disease using intelligent methods

A Singh, P Nath, V Singhal, D Anand, S Verma… - IEEE …, 2020 - ieeexplore.ieee.org
Nonalcoholic Fatty Liver Disease (NAFLD) is the most common cause of chronic liver
disease around the world. Remaining silent in the early stages makes its evaluation a …

A non-singleton type-2 fuzzy neural network with adaptive secondary membership for high dimensional applications

A Mohammadzadeh, E Kayacan - Neurocomputing, 2019 - Elsevier
This paper develops a non-singleton type-2 fuzzy neural network (NT2FNN) with type-2 3-
dimensional membership functions (MFs) and adaptive secondary membership. A new …

A traffic flow state transition model for urban road network based on Hidden Markov Model

G Zhu, K Song, P Zhang, L Wang - Neurocomputing, 2016 - Elsevier
Traffic guidance and prompt information could induce the change of traffic states on road
sections, and in turn the effects of these changes will be transited to their relative upstream …

Multiobjective optimization based adaptive models with fuzzy decision making for stock market forecasting

B Majhi, CM Anish - Neurocomputing, 2015 - Elsevier
Stock market forecasting is an important and challenging task. Conventional single objective
optimization based adaptive prediction models reported in the literature do not satisfy many …

[PDF][PDF] List of references on evolutionary multiobjective optimization

CAC Coello - URL< http://www. lania. mx/~ ccoello/EMOO …, 2010 - delta.cs.cinvestav.mx
List of References on Evolutionary Multiobjective Optimization Page 1 List of References on
Evolutionary Multiobjective Optimization Carlos A. Coello Coello ccoello@cs.cinvestav.mx …