In order to solve the problem of improper thrust distribution of each thruster of underwater vehicle, the PSO optimization algorithm is used to solve the problem of thrust distribution. According to the spatial layout of the thruster, the algorithm model of the underwater vehicle propulsion system is established. The thrust input is carried out under the broken line search trajectory, and the simulation verifies the thrust allocation results of the PSO algorithm and the traditional pseudo-inverse method. The simulation results show that compared with the traditional algorithm. First of all, the PSO algorithm can set the physical threshold for each thruster to prevent the thruster from having too much thrust. Secondly, it can ensure that the thruster can turn with a reasonable torque to prevent the robot from drifting due to the large thrust gap. This paper provides a theoretical reference for thrust distribution of underwater salvage robot, and has practical engineering significance.

The object of research is based on 1.5 MW wind turbine blade. This paper has carried out the aerodynamic shape optimization design of wind turbine blade. Based on the aerodynamic basic theory of wind turbine blade design and combined with particle swarm optimization algorithm(PSO), the design optimization model of the aerodynamic shape of blade is established. Through this study, the optimization results of the angle inducing ′ and tangential inducing  were obtained. The calculation programs are written and calculated chord length and torsion angle of the blade used by ′ and . The calculation result for the optimized wind turbine was 1.38 MW when the wind speed was 16 m/s. The 8 % error could be considered as an engineering acceptable error and the calculated values can be proved the correctness of the design value.

The discovery of new luminescent materials for use in light-emitting diodes(LEDs) has been of great interest, since LED-based solid state lighting applications are attracting a lot of attention in the energy saving and environmental fields. Recent research trends have centered on the discovery of new luminescent materials rather than on fine changes in well-known luminescent materials. In a sense, the novelty of our study beyond simple modification or improvement of existing phosphors. A good strategy for the discovery of new fluorescent materials is to introduce activators that are appropriate for conventional inorganic compounds, that have well-defined structures in the crystal structure database, but have not been considered as phosphor hosts. Another strategy is to discover new host compounds with structures that cannot be found in any existing databases. We have pursued these two strategies at the same time using composite search technology with particle swarm optimization(PSO). In this study, using PSO, we have tracked down a search space composed of Sr-Al-Si-O-N and have discovered a new phosphor structure with yellow luminescence; this material is a potential candidate for UV-LED applications

The object of research in Based on 1.5MW wind turbine blade. This paper has carried out the aerodynamic shape optimization design of wind turbine blade. Based on the aerodynamic basic theory of wind turbine blade design and combined with particle swarm optimization algorithm, the design optimization model of the aerodynamic shape of blade is established. The calculation programs are written by use of MATLAB and calculate chord length and torsion angle of the blade. Then the shape of wind turbine blade is obtained. As research we can know that the chord length is decreased after optimization design of wind turbine blade, The optimized blade not only meets the actual manufacturing requirement, but also has the largest wind energy utilization coefficient.

Recently, owing to the development of ICT industry and wide spread of smart phone, the number of people who use car sharing service are increased rapidly. Currently two-way car sharing system with same rental and return locations are mainly operated since this system can be easily implemented and maintained. Currently the demand of one-way car sharing service has increase explosively. But this system have several obstacle in operation, especially, vehicle stock imbalance issues which invoke vehicle relocation. Hence in this study, we present an optimization approach to depot location and relocation policy in one-way car sharing systems. At first, we modelled as mixed-integer programming models whose objective is to maximize the profits of a car sharing organization considering all the revenues and costs involved and several constraints of relocation policy. And to solve this problem efficiently, we proposed a new method based on particle swarm optimization, which is one of powerful meta-heuristic method. The practical usefulness of the approach is illustrated with a case study involving satellite cities in Seoul Metrolitan Area including several candidate area where this kind systems have not been installed yet and already operating area. Our proposed approach produced plausible solutions with rapid computational time and a little deviation from optimal solution obtained by CPLEX Optimizer. Also we can find that particle swarm optimization method can be used as efficient method with various constraints. Hence based on this results, we can grasp a clear insight into the impact of depot location and relocation policy schemes on the profitability of such systems.

본 연구는 다목적함수를 고려한 입자군집최적화(Particle Swarm Optimization, PSO) 알고리즘을 Python으로 개발하고, Soil and Water Assessment Tool (SWAT) 모형에 적용하여 자동보정 알고리즘의 적용 가능성을 평가하였다. SWAT 모형의 유출 해석은 안성천의 공도 수위 관측소 상류유역(364.8 km2)을 대상으로 하였으며, 공도 지점의 2000년부터 2015년까지의 일 유량 자료를 이용하였다. PSO 자동보정은 결정계수 (coefficient of determination, R2), 평균제곱근오차(RMSE), NSE 모형효율계수(Nash-Sutcliffe Efficiency, NSEQ), 특히 중간유출과 기저유출의 보정을 위해 NSEINQ (Inverse Q)를 활용하여 SWAT을 보정하였다. PSO을 통한 SWAT 모형의 자동보정과 수동보정의 유출해석 결과, 각각 R2 는 0.64, 0.55, RMSE는 0.59, 0.58, NSEQ는 0.78, 0.75, NSEINQ는 0.45, 0.09의 상관성 분석결과를 보였다. PSO 자동보정 알고리즘은 수동보정에 비하여 높은 향상을 보였는데 특히 유출의 감수곡선을 개선시켰으며 적절한 매개변수 추가(RCHRG_DP)와 매개변수 범위의 설정으로 수동 보정의 한계를 보완하였다.

In this paper, we propose remote navigation control for intelligent robot using particle swarm optimization(PSO). The proposed system consists of interfaces for intelligent robot navigation and user interface in order to control the intelligent robot remotely. And communication interfaces using TCP/IP socket is used. To do this, we first design the fuzzy navigation controller based on expert's knowledge for intelligent robot navigation. At this time, we use the PSO algorithm in order to identify the membership functions of fuzzy control rules. And then, we propose the remote system in order to navigate the robot remotely. Finally, we show the effectiveness and feasibility of the developed controller and remote system through some experiments.