Distant luminous quasars provide important information on the growth of the first supermassive black holes, their host galaxies and the epoch of reionization. The identification of quasars is usually performed through detection of their Lyman-α line redshifted to 0.9 microns at z > 6.5. Here, we report the discovery of a very Lyman-α luminous quasar, PSO J006.1240 + 39.2219 at redshift z = 6.61...

Inertia weight is one of the most important adjustable parameters of particle swarm optimization (PSO). The proper selection of inertia weight can prove a right balance between global search and local search. In this paper, a novel PSOs with non-linear inertia weight based on the arc tangent function is provided. The performance of the proposed PSO models are compared with standard PSO with lin...

Particle Swarm Optimization (PSO) has shown its good search ability in many optimization problems. But PSO easily gets trapped into local optima while dealing with complex problems due to lacks in diversity. In this work, we proposed an improved PSO, namely PSO-APMLB, in which adaptive polynomial mutation strategy is employed in local best of particles to introduce diversity in the swarm space....

This paper proposes a novel application of a chaos particle swarm optimization (PSO) algorithm for tracking a maximum power point (MPP) of a solar photovoltaic (PV) panel under varying atmospheric conditions. Solar PV cells have a nonlinear V-I characteristic with a distinct MPP which depends on environmental factors such as temperature and irradiation. In order to continuously harvest maximum ...

This paper investigates the application of particle swarm optimization (PSO) to the multi-objective flexible job shop scheduling problem with sequence-dependent set-up times, auxiliary resources and machine down time. To achieve this goal, alternative particle representations and problem mapping mechanisms were implemented within the PSO paradigm. This resulted in the development of four PSO-ba...

It has proposed a kind of hybrid method based on intuitionistic fuzzy set theory and particle swarm optimization (PSO) algorithm-based neural network (NN). We apply it to the integrative damage effect assessment of battlefield target. Firstly, we improve PSO algorithm, propose the adaptive inertia factor and excellence selection mechanism, introduce inter-partition particle swarm initialization...

This paper introduces an intelligent evaluation method based on improved PSO-WNN (partiele swarm optimization-wavelet neural network) for speech denoising in high background noise. Firstly, by using Lyapunov stability theory, convergence conditions of a single particle is discussed and based on the result, a new strategy is introduced to improve the performance of the PSO algorithm. Then, the i...

In this paper, a particle swarm optimization algorithm (PSO) is presented to solve the permutaion flowshop sequencing problem (PFSP) with the objectives of minimizing makespan and maximum lateness of jobs, respectively. Simple but very efficient local search based on variable neighborhood search (VNS) is embedded in the particle swarm optimization algorithm to solve the well known benchmark sui...

This paper proposes a robust H∞ control method for three-phase PWM rectifier. Based on the mathematical model of the PWM rectifier, the state equations which include outside interference are established for the standard setup H∞ control problem with suitable weighting functions. The robust H∞ controller can be derived by solving the Riccati inequality. An improved PSO algorithm is proposed in t...