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Optimizing Internet of Things Fog Computing: Through Lyapunov-Based Long Short-Term Memory Particle Swarm Optimization Algorithm for Energy Consumption Optimization. [PDF]

Sensors (Basel)
Pan S, Huang C, Fan J, Shi Z, Tong J, Wang H.   +5 more
europepmc   +1 more source

Phase Diagrams and Piezoelectric Properties of Wurtzite Al1−x−yScxGdyN Heterostructural Alloys

Advanced Science, EarlyView.
This study demonstrates ferroelectricity and piezoelectric properties improvement of quaternary wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films, guided by density functional theory calculations. Wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films have a high optical bandgap, enhanced piezoelectric ...
Julia L. Martin, Cheng‐Wei Lee, Nate S.P. Bernstein, Thi Nguyen, Ande Bryan, Eli Cooper, John S. Mangum, Sage R. Bauers, Andriy Zakutayev, Keisuke Yazawa, Prashun Gorai, Rebecca W. Smaha   +11 more
wiley   +1 more source

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Optimizing Particle Swarm Optimization algorithm

2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), 2014
Particle Swarm Optimization (PSO) algorithm has become more popular recently. It has been shown to be an effective optimization tool in most of the applications. In this paper, we have applied the PSO algorithm to a sample Artificial Neural Network (ANN) application, measured the improvement, and optimized the PSO parameters to improve results as much ...
Iraj Koohi, Voicu Z. Groza
openaire   +1 more source

An improved particle swarm optimization algorithm

2008 IEEE International Conference on Granular Computing, 2008
An improved Particle Swarm Optimization (IPSO) algorithm is proposed in this paper. In the algorithm, a premature estimate mechanism is introduced to judge whether the particles accumulate in a small region and tell the probability whether the swarm is trapped in a local optimum.
Lin Lu, Qi Luo, Jun-yong Liu, Chuan Long
openaire   +1 more source

A cultural particle swarm optimization algorithm

2010 Sixth International Conference on Natural Computation, 2010
A new culture-based Particle Swarm Optimization (PSO) with mutation, CPSOM, is proposed in this paper to improve the overall optimization performance of the original PSO and combat with the well-known premature problem. In the CPSOM, the Evolutionary Programming (EP) mutation operator is applied to a proportion of the particles in the population space ...
Ying Wu, Xiao Zhi Gao 0001, Xianlin Huang, Kai Zenger   +3 more
openaire   +1 more source

On the improvements of the particle swarm optimization algorithm

Advances in Engineering Software, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ting-Yu Chen, Tzu-Ming Chi
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An improved particle swarm optimization algorithm

2013 Ninth International Conference on Natural Computation (ICNC), 2013
Particles can remember some information in an optimization process. They learn by themselves and from other particles, so the next generation can inherit much information from their parents and finally find optimal solutions. But particles are also faced with two problems of stagnating in a local but not global optimum.
Huafen Yang, Dejian Kong, Zuyuan Yang, You Yang, Dechun Dong, Lihui Zhang   +5 more
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An amelioration Particle Swarm Optimization algorithm

2010 Sixth International Conference on Natural Computation, 2010
a new amelioration Particle Swarm Optimization (SARPSO) based on simulated annealing (SA), asynchronously changed learning genes (ACLG) and roulette strategy was proposed because the classical Particle Swarm Optimization (PSO) algorithm was easily plunged into local minimums.
Huayong Xie, Mingqing Xiao 0003, Bin Hu 0027, Hang Yu   +3 more
openaire   +1 more source