年份 | 2017 |
学科 | 工程力学 Engineering Mechanics |
国家/州 | Sweden |
Can Machines Learn to Design Better than Humans?
While Machine Learning has made great strides in predictions, less research has been done on the application of AI to the engineering design. The purpose of this research was to test machine learning algorithms against expert human designers to see how they would perform.
The question investigated was to test how well machine learning algorithms could perform in the design of complex power trains of racing drones, specifically the selection of brushless motor and propeller combinations to optimize particular design objectives. Racing drones were chosen because of the high stakes of the competition and the high complexity of the engineering problem.
Detailed characteristics and performance data were collected for 16 brushless motors and 18 propellers in more than 112 tests of motor - propeller combinations.From the performance data, three variables were extracted: i) maximum thrust, ii) efficiency, and iii) dynamic punch.The training data was used to train three different machine learning algorithms: Neural Network, Local Weighted Regression, and Boosted Decision Trees.
A testing data set of seven motors and eight propellers was presented to the algorithms to select the best performance combinations. The same choices were presented to eight recognized experts in the field, and their performance was compared against the machine learning algorithms.
Despite some good performances by humans, the AI algorithms beat the best humans in two of the three contests. The machine learning algorithms were particularly impressive in finding the optimal powertrain design to optimize punch - arguably the most important dimension in drone racing.
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英特尔国际科学与工程大奖赛,简称 "ISEF",由美国 Society for Science and the Public(科学和公共服务协会)主办,英特尔公司冠名赞助,是全球规模最大、等级最高的中学生的科研科创赛事。ISEF 的学术活动学科包括了所有数学、自然科学、工程的全部领域和部分社会科学。ISEF 素有全球青少年科学学术活动的“世界杯”之美誉,旨在鼓励学生团队协作,开拓创新,长期专一深入地研究自己感兴趣的课题。
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Studies that focus on the science and engineering that involve movement or structure. The movement can be by the apparatus or the movement can affect the apparatus.
Aerospace and Aeronautical Engineering (AER): Studies involving the design of aircraft and space vehicles and the direction of the technical phases of their manufacture and operation.
Civil Engineering (CIV): Studies that involve the planning, designing, construction, and maintenance of structures and public works, such as bridges or dams, roads, water supply, sewer, flood control and, traffic.
Computational Mechanics (COM): A study that applies the discipline and techniques of computer science and mathematics to solve large and complex problems in Engineering Mechanics.
Control Theory (CON): The study of dynamical systems, including controllers, systems, and sensors that are influenced by inputs.
Ground Vehicle Systems (VEH): The design of ground vehicles and the direction of the technical phases of their manufacture and operation.
Industrial Engineering-Processing (IND): Studies of efficient production of industrial goods as affected by elements such as plant and procedural design, the management of materials and energy, and the integration of workers within the overall system. The industrial engineer designs methods, not machinery.
Mechanical Engineering (MEC): Studies that involve the generation and application of heat and mechanical power and the design, production, and use of machines and tools.
Naval Systems (NAV): Studies of the design of ships and the direction of the technical phases of their manufacture and operation.
Other (OTH): Studies that cannot be assigned to one of the above subcategories. If the project involves multiple subcategories, the principal subcategory should be chosen instead of Other.
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