| Project/Area Number |
13680451
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Kyushu University(Faculty of Design) |
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Principal Investigator |
TAKAGI Hideyuki Kyushu University, Faculty of Design, Associate Professor, 大学院・芸術工学研究院, 助教授 (50274543)
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| Project Period (FY) |
2001 – 2003
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| Project Status |
Completed (Fiscal Year 2003)
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| Budget Amount *help |
¥2,700,000 (Direct Cost: ¥2,700,000)
Fiscal Year 2003: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2002: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2001: ¥900,000 (Direct Cost: ¥900,000)
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| Keywords | interactive evolutionary computation / visualization / optimization / physiological measurement / 心理計測 / 対話型進化計算 / 進化計算 / Visualized IEC |
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| Research Abstract |
This research consists of three parts.
The first part is the proposal of visualized interactive evolutionary computation (Visualized IEC) that visualizes the landscape of an EC search space and the evaluation of its effectiveness. Human IEC user and EC play independent roles of evaluation and optimization in a basic IEC approach, respectively. We proposed a method that maps an EC landscape into a 2-D space for visualizing the landscape, displays the visualized EC landscape to a human user, and let the user join to the EC optimization process. We compared four mapping methods from the computational cost and convergence speed point of view and concluded that the Visualized IEC with SOM (Self-Organized Map) is the best practical implementation among the four mapping methods.
The second part is the development of this visualization approach. First, we implemented the Visualized IEC into a PDA for reducing the restrictions of place and time of hearing-aid fitting and evaluated the practicalne
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ss of the EC-based hearing-aid fitting method. Second, we proposed an acceleration method of EC convergence by using EC landscape information. We evaluated the method that estimates a global optimum area by approximating an EC landscape using a single-peak function and used the estimated global optimum as an elite individual in the next generation, the method that approximates an EC landscape with multiple Gaussian functions as well and generates offspring by using the functions as random Gaussian noise generators, and other methods. Third, we applied an IEC technique to design medical image enhancement filters visually for increasing the intelligibility of the images for medical diagnostics. We showed its effectiveness by using a medical image diagnostic expert who is not an expert of image signal processing as an IEC experimental subject.
The third part is the investigation of the IEC applicability to the visualization of mental condition. We had 3 schizophrenics and 5 mental-normals design 'happy' and 'sad' computer graphics (CG) lightings with an IEC-based CG lighting design support system and had 32 subjects evaluate their designs with a paired comparison method. This experimental result showed that the dynamic expression ranges of "happy -sad" of the schizophrenics were narrower than those of mental-normals significantly. It means that the IEC technique can be a capable tool for measuring human mind situation. Less
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