✦ LIBER ✦

Optimal design of electric machine using genetic algorithms coupled with direct method

✍ Scribed by Yong-Hwan Oh, ; Tae-Kyung Chung, ; Min-Kyu Kim, ; Hyun-Kyo Jung,

Book ID: 126051977
Publisher: IEEE
Year: 1999
Tongue: English
Weight: 348 KB
Volume: 35
Category: Article
ISSN: 0018-9464
DOI: 10.1109/20.767366

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Design optimization of electrical machin

Design optimization of electrical machines using genetic algorithms

✍ Uler, G.F.; Mohammed, O.A.; Chang-Seop Koh 📂 Article 📅 1995 🏛 IEEE 🌐 English ⚖ 486 KB

Inverse shape optimization using dynamic

Inverse shape optimization using dynamically adjustable genetic algorithms [electric machine design]

✍ Cingoski, V.; Kaneda, K.; Yamashita, H.; Kowata, N. 📂 Article 📅 1999 🏛 IEEE 🌐 English ⚖ 679 KB

Parallel optimal statistical design meth

Parallel optimal statistical design method with response surface modelling using genetic algorithms

✍ Wu, A.; Wu, K.Y.; Chen, R.M.M.; Shen, Y. 📂 Article 📅 1998 🏛 The Institution of Electrical Engineers 🌐 English ⚖ 681 KB

Optimal Design of an SPM Motor Using Gen

Optimal Design of an SPM Motor Using Genetic Algorithms and Taguchi Method

✍ Chang-Chou Hwang, ; Li-Yang Lyu, ; Cheng-Tsung Liu, ; Ping-Lun Li, 📂 Article 📅 2008 🏛 IEEE 🌐 English ⚖ 419 KB

Direct use of design criteria in genetic

Direct use of design criteria in genetic algorithm-based controller optimization

✍ Yoon-Jun Kim; Jamshid Ghaboussi 📂 Article 📅 2001 🏛 John Wiley and Sons 🌐 English ⚖ 138 KB 👁 2 views

A solution method for optimal weight des

A solution method for optimal weight design problem of the gear using genetic algorithms

✍ Takao Yokota; Takeaki Taguchi; Mitsuo Gen 📂 Article 📅 1998 🏛 Elsevier Science 🌐 English ⚖ 264 KB

In this paper, we formulate an optimal weight designproblem of a gear for a constrained bending strength of gear, tortional strength of shafts and each gear dimension as a nonlinear integer programing(NIP) problemand solve it directly by keeping the nonlinear constraint by using an improved genetic