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 …
Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges
The integration of large-scale wind power introduces issues in modern power systems
operations due to its strong randomness and volatility. These issues can be resolved via …
operations due to its strong randomness and volatility. These issues can be resolved via …
Forecasting of future greenhouse gas emission trajectory for India using energy and economic indexes with various metaheuristic algorithms
The accelerating increment of greenhouse gas (GHG) concentration in the atmosphere
already reached an alarming level, and nowadays its adverse impacts on the living …
already reached an alarming level, and nowadays its adverse impacts on the living …
Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives
S Sengupta, S Basak, RA Peters - Machine Learning and Knowledge …, 2018 - mdpi.com
Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has
gained prominence in the last two decades due to its ease of application in unsupervised …
gained prominence in the last two decades due to its ease of application in unsupervised …
A comprehensive survey on particle swarm optimization algorithm and its applications
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
Forecasting methods in energy planning models
KB Debnath, M Mourshed - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy planning models (EPMs) play an indispensable role in policy formulation and energy
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
Forecasting energy consumption using ensemble ARIMA–ANFIS hybrid algorithm
S Barak, SS Sadegh - International Journal of Electrical Power & Energy …, 2016 - Elsevier
Energy consumption is on the rise in developing economies. In order to improve present and
future energy supplies, forecasting energy demands is essential. However, lack of accurate …
future energy supplies, forecasting energy demands is essential. However, lack of accurate …
Multifactor-influenced energy consumption forecasting using enhanced back-propagation neural network
Reliable energy consumption forecasting can provide effective decision-making support for
planning development strategies to energy enterprises and for establishing national energy …
planning development strategies to energy enterprises and for establishing national energy …
Short term electric load forecasting model and its verification for process industrial enterprises based on hybrid GA-PSO-BPNN algorithm—A case study of …
Process industry consumes tremendous amounts of electricity for production. Electric load
forecasting could be conducive to managing the electricity consumption, determining the …
forecasting could be conducive to managing the electricity consumption, determining the …
On the evaluation of the viscosity of nanofluid systems: Modeling and data assessment
A Hemmati-Sarapardeh, A Varamesh… - … and Sustainable Energy …, 2018 - Elsevier
Viscosity of nanofluids can significantly affect pumping power, pressure drop, workability of
the nanofluid as well as its convective heat transfer coefficient. Experimental measurements …
the nanofluid as well as its convective heat transfer coefficient. Experimental measurements …