25 years of particle swarm optimization: Flourishing voyage of two decades
From the past few decades many nature inspired algorithms have been developed and
gaining more popularity because of their effectiveness in solving problems of distinct …
gaining more popularity because of their effectiveness in solving problems of distinct …
A novel particle swarm optimization algorithm with Levy flight
Particle swarm optimization (PSO) is one of the well-known population-based techniques
used in global optimization and many engineering problems. Despite its simplicity and …
used in global optimization and many engineering problems. Despite its simplicity and …
Day-ahead load forecast using random forest and expert input selection
The electrical load forecast is getting more and more important in recent years due to the
electricity market deregulation and integration of renewable resources. To overcome the …
electricity market deregulation and integration of renewable resources. To overcome the …
A novel combined model based on hybrid optimization algorithm for electrical load forecasting
R Wang, J Wang, Y Xu - Applied Soft Computing, 2019 - Elsevier
Accurate electrical load forecasting always plays a vital role in power system administration
and energy dispatch, which are the foundation of the smooth operation of the national …
and energy dispatch, which are the foundation of the smooth operation of the national …
A Takagi–Sugeno fuzzy model combined with a support vector regression for stock trading forecasting
PC Chang, JL Wu, JJ Lin - Applied soft computing, 2016 - Elsevier
The turning points prediction scheme for future time series analysis based on past and
present information is widely employed in the field of financial applications. In this research …
present information is widely employed in the field of financial applications. In this research …
[HTML][HTML] A hybrid application algorithm based on the support vector machine and artificial intelligence: An example of electric load forecasting
Y Chen, Y Yang, C Liu, C Li, L Li - Applied Mathematical Modelling, 2015 - Elsevier
Accurate electric load forecasting could prove to be a very useful tool for all market
participants in electricity markets. Because it can not only help power producers and …
participants in electricity markets. Because it can not only help power producers and …
Random forests model for one day ahead load forecasting
Short term load forecasting is one of the most important tasks for power suppliers, and it is
getting more important with deregulation of electricity market and emergence of smart grids …
getting more important with deregulation of electricity market and emergence of smart grids …
Fuzzy transfer learning: methodology and application
J Shell, S Coupland - Information Sciences, 2015 - Elsevier
Producing a methodology that is able to predict output using a model is a well studied area
in Computational Intelligence (CI). However, a number of real-world applications require a …
in Computational Intelligence (CI). However, a number of real-world applications require a …
MultiCycleNet: multiple cycles self-boosted neural network for short-term electric household load forecasting
Household load forecasting plays an important role in future grid planning and operation.
However, compared with aggregated load forecasting, household load forecasting faces the …
However, compared with aggregated load forecasting, household load forecasting faces the …
Improving Wang–Mendel method performance in fuzzy rules generation using the fuzzy C-means clustering algorithm
J Gou, F Hou, W Chen, C Wang, W Luo - Neurocomputing, 2015 - Elsevier
The generation of fuzzy rules from samples for fuzzy modeling and control is significant. If
samples contain noise and outliers, the Wang–Mendel (WM) method may lead to the …
samples contain noise and outliers, the Wang–Mendel (WM) method may lead to the …