Optimizing Available Transfer Capability Based on Chaos Cloud Particle Swarm Algorithm with Gold Section Criteria
نویسندگان
چکیده
منابع مشابه
A Chaos Cloud Particle Swarm Algorithm Based Available Transfer Capability
A mathematical model for ATC based on optimal power flow was built under the static security constraints, where the maximum of all load nodes in receiving area was considered as aim function. In view of the defects of slow convergence and low accuracy in ATC optimization algorithms, a chaos cloud particle swarm optimization algorithm based on golden section criteria (CCGPSO) was proposed. This ...
متن کاملThe K-means Clustering Algorithm Based on Chaos Particle Swarm
Proposed the Algorithm of K-means (CPSOKM) based on Chaos Particle Swarm in order to solve the problem that K-means algorithm sensitive to initial conditions and is easy to influence the clustering effect. On the selection of the initial value problem, algorithm using particle swarm algorithm to balance the random value uncertainty, and then by introducing a chaotic sequence, the particles move...
متن کاملHybrid Mutation Particle Swarm Optimisation Method for Available Transfer Capability Enhancement
A Hybrid Mutation Particle Swarm Optimisation (HMPSO) technique for improved estimation of Available Transfer Capacity (ATC) as a decision criterion is proposed in this paper. First, this is achieved by comparing a typical application of the Particle Swarm Optimisation (PSO) technique with conventional Genetic Algorithm (GA) methods. Next, a multi-objective optimisation problem concerning optim...
متن کاملAn Improved Quantum-behaved Particle Swarm Optimization Algorithm Based on Chaos Theory Exerting to Particle Position
In this paper, we propose an improved quantum-behaved particle swarm optimization (QPSO), introducing chaos theory into QPSO and exerting logistic map to every particle position X(t) at a certain probability. In this improved QPSO, the logistic map is used to generate a set of chaotic offsets and produce multiple positions around X(t). According to their fitness, the particle's position is upda...
متن کاملResearch of Blind Signals Separation with Genetic Algorithm and Particle Swarm Optimization Based on Mutual Information
Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Security and Its Applications
سال: 2017
ISSN: 1738-9976,1738-9976
DOI: 10.14257/ijsia.2017.11.4.05