{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T19:09:16Z","timestamp":1724958556605},"reference-count":24,"publisher":"IGI Global","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,4,1]]},"abstract":"<p>Interactive Evolutionary Computation (IEC) is known as an effective method to create media contents suited to user\u2019s preference and objectives. As one of the methods, we have applied Differential Evolution (DE) as evolutionary algorithm in IEC. This study investigated the efficacy of Interactive Differential Evolution (IDE) in comparison with Interactive Genetic Algorithm (IGA). Two listening experiments were conducted to investigate the efficacy: experiment 1 as a creating experiment with IDE and IGA, experiment 2 as a re-evaluating experiment. Target of the creation was warning sign sounds. Eighteen subjects participated in both of the experiments. The result of the experiment 1 showed that IDE overcame IGA, and significant increase of fitness was only observed in IDE. The result of the experiment 2, higher fitness value was observed in IDE, however, the difference between the two conditions was not significant. Parts of the results showed a possibility of IDE to create media contents.<\/p>","DOI":"10.4018\/ijsi.2013040102","type":"journal-article","created":{"date-parts":[[2013,10,16]],"date-time":"2013-10-16T15:04:21Z","timestamp":1381935861000},"page":"16-27","source":"Crossref","is-referenced-by-count":15,"title":["The Efficiency of Interactive Differential Evolution in Creation of Sound Contents"],"prefix":"10.4018","volume":"1","author":[{"given":"Makoto","family":"Fukumoto","sequence":"first","affiliation":[{"name":"Fukuoka Institute of Technology, Fukuoka, Japan"}]},{"given":"Ryota","family":"Yamamoto","sequence":"additional","affiliation":[{"name":"Fukuoka Institute of Technology, Fukuoka, Japan"}]},{"given":"Shintaro","family":"Ogawa","sequence":"additional","affiliation":[{"name":"Fukuoka Institute of Technology, Fukuoka, Japan"}]}],"member":"2432","reference":[{"key":"ijsi.2013040102-0","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-68830-3"},{"key":"ijsi.2013040102-1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2010.2059031"},{"key":"ijsi.2013040102-2","author":"R.Dawkins","year":"1986","journal-title":"The blind watchmaker"},{"key":"ijsi.2013040102-3","unstructured":"Fukumoto, M., Hazama, T., & Imai, J. (2008). Evolutionary computation for creating musical melody based on user's physiological index. In Proceedings of the Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS&ISIS2008) (pp. 247-252)."},{"key":"ijsi.2013040102-4","unstructured":"Fukumoto, M., & Imai, J. (2010). Design of scents suited with user's kansei using interactive evolutionary computation. In Proceedings of the International Conference on Kansei Engineering and Emotion Research 2010, (pp. 1016-1022)."},{"key":"ijsi.2013040102-5","doi-asserted-by":"crossref","unstructured":"Fukumoto, M., Inoue, M., & Imai, J. (2010). User's favorite scent design using paired comparison-based interactive differential evolution. 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H.Holland","year":"1975","journal-title":"Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control and artificial intelligence"},{"key":"ijsi.2013040102-12","doi-asserted-by":"crossref","unstructured":"Miki, M., Orita, H., Wake, S. H., & Hiroyasu, T. (2006). Design of sign sounds using an interactive genetic algorithm. In Proceedings of the IEEE International Conference on SMC2006 (Vol. 4, pp. 3486-3490).","DOI":"10.1109\/ICSMC.2006.384659"},{"key":"ijsi.2013040102-13","first-page":"653","article-title":"An IEC-based haptic rendering optimizer.","volume":"05","author":"H.Nishino","year":"2005","journal-title":"Proceedings of the IEEE WSTST"},{"key":"ijsi.2013040102-14","doi-asserted-by":"crossref","unstructured":"Ogawa, S., & Fukumoto, M. (2011). Proposal for creation of various sign sounds using interactive genetic algorithm. IEEJ Transactions, EIS, 131(3), 698-699 (in Japanese).","DOI":"10.1541\/ieejeiss.131.698"},{"key":"ijsi.2013040102-15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-92151-6"},{"key":"ijsi.2013040102-16","author":"C. E.Osgood","year":"1957","journal-title":"The measurement of meaning"},{"key":"ijsi.2013040102-17","author":"K. V.Price","year":"2005","journal-title":"Differential evolution\u2013A practical approach to global optimization"},{"key":"ijsi.2013040102-18","doi-asserted-by":"crossref","unstructured":"Ronkkonen, J., Kukkonen, S., & Price, K. V. (2005). Real-parameter optimization with differential evolution. In Proceedings of the 2005 IEEE Congress on Evolutionary Computation (Vol. 1, pp. 506-513.","DOI":"10.1109\/CEC.2005.1554725"},{"key":"ijsi.2013040102-19","unstructured":"Storn, R., & Price, K. V. (1995). Differential evolution\u2013A simple and efficient adaptive scheme for global optimization over continuous spaces. Institute of Company Secretaries of India, Chennai, Tamil Nadu (Tech. Report TR-95-012)."},{"key":"ijsi.2013040102-20","doi-asserted-by":"publisher","DOI":"10.1109\/5.949485"},{"key":"ijsi.2013040102-21","doi-asserted-by":"crossref","unstructured":"Takagi, H., & Pallez, D. (2009). Paired comparison-based interactive differential evolution. In Proceedings of the World Congress on Nature and Biologically Inspired Computing (pp. 375-380).","DOI":"10.1109\/NABIC.2009.5393359"},{"key":"ijsi.2013040102-22","unstructured":"Takekata, K., Salzman, B. A., Nishino, H., Kagawa, T., & Utsumiya, K. (2005). An intuitive optimazation method of haptic rendering using interactive evolutionary computation. In Proceedings of the IEEE International Conference on SMC2005 (pp. 1896-1901)."},{"key":"ijsi.2013040102-23","doi-asserted-by":"crossref","unstructured":"Vesterstr\u00f8m, J., & Thomson, R. (2004). A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems. 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