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...

يا هچروم يدنب هشوخ متيروگلا ياراد پ ا ار يددعتم ياهرتم هلمج زا ،نتشادرب هب طوبرم ياهرتماراپ نتشاذگ اه هداد ديد عاعش ، يم هك دشاب ريثات و دنراد متيروگلا ييارگمه و دركلمع رد يدايز اطخ و شيامزآ تروص هب لاومعم نييعت يم رگ د دن . شور هلاقم نيا رد ي رب ينتبم CLA-PSO 1 ي هتسسگ لدم كي هك PSO دشاب يم يارب قيبطت كيتاموتا پ ياهرتمارا يا هچروم يدنب هشوخ يم داهنشيپ ددرگ . روظنم هب گلا ساسا رب هك د...

The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the ...

Particle swarm optimization (PSO) is a population based statistical optimization technique which is inspired by social behavior of bird flocking or fish schooling. The main weakness of PSO especially in multimodal problems is trapping in local minima. Recently a learning automata based PSO called PSO-LA to improve the performance of PSO has been reported. PSO-LA uses one learning automaton for ...

This paper presents a designing an optimal adaptive controller for tracking down the control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been used to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using a logic is proposed to increase the c...

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method developed in 1995 by Eberhart and Kennedy based on the social behaviors of birds flocking or fish schooling. A number of basic variations have been developed due to improve speed of convergence and quality of solution found by the PSO. On the other hand, basic PSO is more appropriate to pro...

This paper investigates into hybridization between PSO and self-adaptive evolutionary programming techniques for solving economic dispatch (ED) problem with non-smooth cost curves where conventional gradient based methods are in-applicable. The convergence capability of evolutionary programming technique is enhanced with hybridization of self-adaptive evolutionary programming technique with PSO...

this paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (pso) algorithm. pso algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ise) as a performance criteria. in this paper, an improved pso using logic is proposed to increase the convergenc...

In this paper we investigate the application of the Particle Swarm Optimization (PSO) technique for solving the Hardware/Software partitioning problem. The PSO is attractive for the Hardware/Software partitioning problem as it offers reasonable coverage of the design space together with O(n) main loop's execution time, where n is the number of proposed solutions that will evolve to provide the ...

This paper proposes an energy efficient control strategy for an induction machine (IM) based on two advanced particle swarm optimisation (PSO) algorithms. Two advanced PSO algorithms, known as the dynamic particle swarm optimisation (Dynamic PSO) and the chaos particle swarm optimisation (Chaos PSO) algorithms modify the algorithm parameters to improve the performance of the standard PSO algori...