CCGPA‐MPPT: Cauchy preferential crossover‐based global pollination algorithm for MPPT in photovoltaic system

V Sundararaj, V Anoop, P Dixit, A Arjaria… - Progress in …, 2020 - Wiley Online Library
In general, the photovoltaic (PV) is considered as the best selection among renewable
energy resources due to its nonpolluted operation and good flexibility condition. The PV …

Day-ahead load forecast using random forest and expert input selection

A Lahouar, JBH Slama - Energy Conversion and Management, 2015 - Elsevier
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 …

Daily PM2. 5 concentration prediction based on principal component analysis and LSSVM optimized by cuckoo search algorithm

W Sun, J Sun - Journal of environmental management, 2017 - Elsevier
Increased attention has been paid to PM 2.5 pollution in China. Due to its detrimental effects
on environment and health, it is important to establish a PM 2.5 concentration forecasting …

Hybrid bio-Inspired computational intelligence techniques for solving power system optimization problems: A comprehensive survey

I Rahman, J Mohamad-Saleh - Applied Soft Computing, 2018 - Elsevier
Optimization problems of modern day power system are very challenging to resolve
because of its design complexity, wide geographical dispersion and influence from many …

Traffic flow forecasting by a least squares support vector machine with a fruit fly optimization algorithm

Y Cong, J Wang, X Li - Procedia Engineering, 2016 - Elsevier
The accuracy of traffic flow forecasting plays an important role in the field of modern
Intelligent Transportation Systems (ITS). The least squares support vector machine (LSSVM) …

A least squares support vector machine model optimized by moth-flame optimization algorithm for annual power load forecasting

C Li, S Li, Y Liu - Applied Intelligence, 2016 - Springer
Annual power load forecasting is essential for the planning, operation and maintenance of
an electric power system, which can also mirror the economic development of a country to …

Short-term traffic flow prediction based on least square support vector machine with hybrid optimization algorithm

C Luo, C Huang, J Cao, J Lu, W Huang, J Guo… - Neural processing …, 2019 - Springer
Accurate short-term traffic flow prediction plays an indispensable role for solving traffic
congestion. However, the structure of traffic data is nonlinear and complicated. It is a …

Annual electric load forecasting by a least squares support vector machine with a fruit fly optimization algorithm

H Li, S Guo, H Zhao, C Su, B Wang - Energies, 2012 - mdpi.com
The accuracy of annual electric load forecasting plays an important role in the economic and
social benefits of electric power systems. The least squares support vector machine …

Prediction of dissolved oxygen content in river crab culture based on least squares support vector regression optimized by improved particle swarm optimization

S Liu, L Xu, D Li, Q Li, Y Jiang, H Tai, L Zeng - Computers and Electronics in …, 2013 - Elsevier
It is important to set up a precise predictive model to obtain clear knowledge of the
prospective changing conditions of dissolved oxygen content in intensive aquaculture ponds …

Experimental observations and SVM-based prediction of properties of polypropylene fibres reinforced self-compacting composites incorporating nano-CuO

F Naseri, F Jafari, E Mohseni, W Tang… - … and Building Materials, 2017 - Elsevier
This paper presents an experimental study to examine the hardened and fresh properties of
self-compacting concrete (SCC) containing nano-CuO (NC) and polypropylene (PP) fibres …