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All Technical Committee Conferences (All Years)
| 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 |
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