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RISS 인기검색어
- 검색키워드
- 저자 : Yoshiaki Toyoda (검색결과 5 건)
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Toyoda, Yoshiaki,Yano, Fumihiko Korean Institute of Industrial Engineers 2004 Industrial Engineeering & Management Systems Vol.3 No.1
To optimize movement of a multi-joint robot arm is known to be a difficult problem, because it is a kind of redundant system. Although the end-effector is set its position by each angle of the joints, the angle of each joint cannot be uniquely determined by the position of the end-effector. There exist the infinite number of different sets of joint angles which represent the same position of the end-effector. This paper describes how to manage the angle of each joint to move its end-effector preferably on an X-Y plane with obstacles in the end-effector’s reachable area, and how to optimize the movement of a multi-joint robot arm, evading obstacles. The definition of “preferable” movement depends upon a purpose of robot operation. First, we divide viewpoints of preference into two, 1) the standpoint of the end-effector, and 2) the standpoint of joints. Then, we define multiple objective functions, and formulate it into a multi-objective programming problem. Finally, we solve it using multi-purpose genetic algorithm, and obtain reasonable results. The method described here is possible to add appropriate objective function if necessary for the purpose.
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In-plane Anisotropy of the Magnetic and the Electric Properties of the Fe Pnictide Ba(Fe1−xCox)2As2
Yoshiaki Kobayashi,Akihiro Ichikawa,Masayuki Toyoda,Masayuki Itoh,Masatoshi Sato 한국물리학회 2013 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.63 No.3
The anisotropy of the electronic and the magnetic properties within the FeAs planes of Co(2%)-doped BaFe2As2 has been investigated by using 75As nuclear magnetic resonance (NMR) measurementson the As (As0) sites with all four nearest neighbor sites occupied by Fe. Even in thetetragonal phase at temperatures above 100 K, two sets of NMR spectra with twofold symmetry ofin-plane Knight shifts and electronic nuclear quadrupole frequencies are observed. They originatefrom two domains with their symmetry axes lying at right angles to each other. The anisotropies ofthe electronic and the magnetic properties become pronounced at 140 K, below which an in-planeanisotropy is reported to appear in electrical resistivity under a pressure along one of Fe-Fe directions. 75As NMR measurements have also been carried out for the As (As1) sites surrounded byone Co and three Fe. From the data, we conclude that the spin susceptibility of As1 is ~1/3 thatof As0 and that the antiferromagnetic spin fluctuation of As1 is fairly suppressed as compared withthat of As0. We discuss these behaviors of the FeAs layer in connection with the impurity-inducedlocal orbital order model proposed by theoretical studies.
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An Improvement of Particle Swarm Optimization with A Neighborhood Search Algorithm
Fumihiko Yano,Tsutomu Shohdohji,Yoshiaki Toyoda 대한산업공학회 2007 Industrial Engineeering & Management Systems Vol.6 No.1
J. Kennedy and R. Eberhart first introduced the concept called as Particle Swarm Optimization (PSO). They applied it to optimize continuous nonlinear functions and demonstrated the effectiveness of the algorithm. Since then a considerable number of researchers have attempted to apply this concept to a variety of optimization problems and obtained reasonable results. In PSO, individuals communicate and exchange simple information with each other. The information among individuals is communicated in the swarm and the information between individuals and their swarm is also shared. Finally, the swarm approaches the optimal behavior. It is reported that reasonable approximate solutions of various types of test functions are obtained by employing PSO. However, if more precise solutions are required, additional algorithms and/or hybrid algorithms would be necessary. For example, the heading vector of the swarm can be slightly adjusted under some conditions. In this paper, we propose a hybrid algorithm to obtain more precise solutions. In the algorithm, when a better solution in the swarm is found, the neighborhood of a certain distance from the solution is searched. Then, the algorithm returns to the original PSO search. By this hybrid method, we can obtain considerably better solutions in less iterations than by the standard PSO method.
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An Improvement of Particle Swarm Optimization with A Neighborhood Search Algorithm
Yano, Fumihiko,Shohdohji, Tsutomu,Toyoda, Yoshiaki Korean Institute of Industrial Engineers 2007 Industrial Engineeering & Management Systems Vol.6 No.1
J. Kennedy and R. Eberhart first introduced the concept called as Particle Swarm Optimization (PSO). They applied it to optimize continuous nonlinear functions and demonstrated the effectiveness of the algorithm. Since then a considerable number of researchers have attempted to apply this concept to a variety of optimization problems and obtained reasonable results. In PSO, individuals communicate and exchange simple information with each other. The information among individuals is communicated in the swarm and the information between individuals and their swarm is also shared. Finally, the swarm approaches the optimal behavior. It is reported that reasonable approximate solutions of various types of test functions are obtained by employing PSO. However, if more precise solutions are required, additional algorithms and/or hybrid algorithms would be necessary. For example, the heading vector of the swarm can be slightly adjusted under some conditions. In this paper, we propose a hybrid algorithm to obtain more precise solutions. In the algorithm, when a better solution in the swarm is found, the neighborhood of a certain distance from the solution is searched. Then, the algorithm returns to the original PSO search. By this hybrid method, we can obtain considerably better solutions in less iterations than by the standard PSO method.
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