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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 52  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, MBE
(Joint)
2021-03-03
16:25
Online Online Realization of Global Search and Local Search in Particle Multi-Swarm Optimization
Hiroshi Sho (Kyutech) NC2020-53
For improving search performance and accuracy of pattern classification, this paper proposes a mixed search method of gl... [more] NC2020-53
pp.59-64
SeMI 2021-01-20
13:00
Online Online Swarm Mobility Control for Searching Targets over Unknown Environments
Kengo Ieshima, Hiroyuki Yomo, Yasuhisa Takizawa (Kansai Univ.) SeMI2020-43
In mobile sensing, which conducts sensing operations by installing a sensor on an autonomous mobile robot, the position ... [more] SeMI2020-43
pp.1-6
MBE, NC, NLP, CAS
(Joint) [detail]
2020-10-30
16:10
Online Online Solving the Parity Problem by Particle Multi-Swarm Optimization
Hiroshi Sho (Kyutech) NC2020-24
In recent years, the technology of particle swarm optimization is expanding remarkably. Especially, the technical develo... [more] NC2020-24
pp.83-88
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2020-06-29
13:25
Online Online A Study on Centralized and Distributed Intelligent Particle Multi-Swarm Optimization
Hiroshi Sho (Kyutech) NC2020-3 IBISML2020-3
In this paper, we propose a new method of distributed intelligent particle multi-swarm optimization (DIPMSO) contrast to... [more] NC2020-3 IBISML2020-3
pp.15-20
NC, MBE
(Joint)
2020-03-05
14:15
Tokyo University of Electro Communications
(Cancelled but technical report was issued)
NC2019-97 The purpose of this study is to clarify the search performance and characteristics of differential evolution (DE) and pa... [more] NC2019-97
pp.125-130
SeMI 2020-01-30
14:25
Kagawa   Impact of mutual assistance of mobile robots in mobile sensing cluster exploiting swarm intelligence
Kazuki Higashitani, Eiji Nii, Hiroyuki Yomo, Yasuhisa Takizawa (Kansai Univ.) SeMI2019-100
In mobile sensing, in which autonomous mobile robots with sensors perform sensing operations, the position and number of... [more] SeMI2019-100
pp.5-10
KBSE 2020-01-25
14:55
Tokyo Kikai-Shinko-Kaikan Bldg. Design and Implementation of Multi-Robot Control System Using Extended PSO Based on Multiple Software Agents
Tomoya Minowa, Kazuki Kanari, Tetsuro Takahashi, Masafumi Goto, Toshihiko Seino, Yasushi Kambayashi (NIT) KBSE2019-43
It is difficult for people to search the site where the building collapsed and rubble was scattered.
In that case, a ro... [more]
KBSE2019-43
pp.31-36
NLP 2019-09-23
13:20
Kochi Eikokuji Campus, University of Kochi Artificial Bee Colony Algorithm Following Time-Varying Solutions
Ken Kamiyotsumoto, Yoko Uwate (Tokushima Univ.), Thomas Ott (ZHAW), Yoshifumi Nishio (Tokushima Univ.) NLP2019-42
Recently , nature-inspired metaheuristic optimization algorithms such as Artificial Bee Colony Algorithm (ABC) is develo... [more] NLP2019-42
pp.37-40
SeMI, RCS, NS, SR, RCC
(Joint)
2019-07-11
10:40
Osaka I-Site Nanba(Osaka) [Poster Presentation] Mobility Control with Swarm Intelligence Searching for Sensing Targets
Kengo Ieshima, Eiji Nii, Hiroyuki Yomo, Yasuhisa Takizawa (Kansai Univ.) RCC2019-32 NS2019-68 RCS2019-125 SR2019-44 SeMI2019-41
In mobile sensing where autonomous mobile robots equipped with sensors perform sensing operations over a sensing field, ... [more] RCC2019-32 NS2019-68 RCS2019-125 SR2019-44 SeMI2019-41
pp.107-112(RCC), pp.133-138(NS), pp.129-134(RCS), pp.139-144(SR), pp.121-126(SeMI)
WPT, EE
(Joint)
2018-10-03
14:40
Kyoto Kyoto Univ. Uji Campus [Special Talk] Power Supply Development using Computational Technologies
Yasumichi Omoto, Yoshihiro Ikushima (OMRON Automotive Electronics) EE2018-21
The high-mix development of onboard power supplies is requested for the increasing of xEV in recent years. On the other ... [more] EE2018-21
pp.17-22
NLP 2018-08-08
15:50
Kagawa Saiwai-cho Campus, Kagawa Univ. Ant Colony Optimization for High Accuracy of Solutions
Ken Kamiyotsumoto (Tokushima Univ.), Thomas Ott (ZHAW), Yoko Uwate, Yoshifumi Nshio (Tokushima Univ.) NLP2018-60
Recently, nature-inspired metaheuristic optimization algorithms such as Ant Colony Optimization
(ACO) is developed. ACO... [more]
NLP2018-60
pp.39-42
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2018-06-13
15:25
Okinawa Okinawa Institute of Science and Technology The Search Performance of Hybrid Particle Swarm Optimizers with Information Sharing
Hiroshi Sho (KIT) NC2018-6
As an earlier study,
author proposed multiple particle swarm optimizers with information sharing,
and showed that the ... [more]
NC2018-6
pp.3-8
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2018-06-13
15:50
Okinawa Okinawa Institute of Science and Technology Use of Multiple Particle Swarm Optimizers with Sensors on Solving Tracking Problems
Hiroshi Sho (KIT) NC2018-7
For realizing better search performance and efficiency, in this paper, author proposes three methods which are multiple ... [more] NC2018-7
pp.9-14
NLP 2018-04-27
16:10
Kumamoto Kumaoto Univ. An ABC Algorithm with Improvement of Tracking Performance to Solutions in Dynamic Optimization Problems
Masato Omika, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2018-26
We propose an ABC algorithm to dynamic optimization problems in this article. The proposed method makes the following tw... [more] NLP2018-26
pp.127-131
MBE, NC, NLP
(Joint)
2018-01-27
10:20
Fukuoka Kyushu Institute of Technology Nonlinear map model optimization method
Kenya Jin'no (NIT) NLP2017-95
In this article, we propose a nonlinear map-model optimization (abbr. NMO) method. The NMO consists of some particle who... [more] NLP2017-95
pp.51-54
MBE, NC, NLP
(Joint)
2018-01-27
13:35
Fukuoka Kyushu Institute of Technology The Search Feature of Particle Swarm Optimizer with Sensors in Dynamic Environment
Hiroshi Sho (KIT) NC2017-63
In order to perform the search of particle swarm optimizer under dynamic environment, as a previous study, author has pr... [more] NC2017-63
pp.77-82
NLP 2017-03-14
10:25
Aomori Nebuta Museum Warasse Search Capability of Random Search PSO with Linked Random Update
Kouhei Sakayori, Masato Kaneko, Toshiya Iwai (Nihon Univ.) NLP2016-107
Particle Swarm Optimization (PSO) is a metaheuristics using the swarm intelligence. Although PSO is usually applied to t... [more] NLP2016-107
pp.7-12
CCS 2017-03-10
11:30
Tokyo ELSI, TITECH [Invited Talk] Nanooptics- and fluidics-based physical implementation of natural intelligence
Toshiharu Saiki (Keio Univ.) CCS2016-48
We attempt to implement natural intelligence into nanoparticle systems that involves optical coherence, fluidic interact... [more] CCS2016-48
pp.19-24
NS, IN
(Joint)
2017-03-03
13:00
Okinawa OKINAWA ZANPAMISAKI ROYAL HOTEL Autonomous distributed control methods for wireless sensor networks based on nonlinear dynamics of frog choruses
Ikkyu Aihara (Tsukuba Univ.), Daichi Kominami, Yasuharu Hirano, Masayuki Murata (Osaka Univ.) IN2016-155
There are about 6500 species of frogs around the world. Most of the frog species are nocturnal in their habitat. In gene... [more] IN2016-155
pp.347-352
MBE, NC
(Joint)
2016-11-19
14:35
Miyagi Tohoku University Multiple Particle Swarm Optimizers Based on Information Sharing
Hiroshi Sho (KyuTech) NC2016-37
In order to improve the search performance of multiple particle swarm optimizers, this paper proposes multiple particle ... [more] NC2016-37
pp.27-32
 Results 1 - 20 of 52  /  [Next]  
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