2018英特尔ISEF获奖作品摘要 计算生物与生物信息学 Intel Finalist Abstract Computational Biology and Bioinformatics

获奖作品基本信息

年份 2018
学科 计算生物与生物信息学 Computational Biology and Bioinformatics
国家/州 United States of America

获奖作品名称

Botanical Biomimicry: Using Genetic Algorithms and Plant Phyllotaxy to Determine Optimum-Efficiency Solar Arrays

获奖作品摘要

With the ever-increasing popularity of renewable energy, many are beginning to explore the possibility of using solar arrays in domestic and/or compact, urban environments. For the average property owner, however, placement of solar arrays can be inconvenient due to the large base surface area required to mount traditional flat PV panels. Therefore, as prices to manufacture and install these arrays plummet drastically, researchers must begin to consider exploring more complex, nontraditional orientations of solar cells that could prove to be more efficient than the classic flat solar panel. A program was created to model and generate digital blueprints for these space-efficient arrays by harnessing the sunlight-collecting power of natural plant growth structures. The program utilizes genetic algorithms to mimic the phyllotaxy of plants in making these arrays, as plants are the preeminent natural example of how to best collect sunlight given limited material and space. After developing the program and running through numerous generations in the genetic algorithm, the generated solar arrays (in the shape of digital plants) overall demonstrated a greater efficiency (i.e. a higher average fitness determined by the program’s fitness algorithm) than typical flat solar arrays that occupied the same base area. This paper focuses on the development of the digital plant environment as well as the process of building and executing the genetic algorithms to search for optimum-efficiency plants.


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ISEF 简介

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 的竞赛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竞赛的“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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英特尔 ISEF 竞赛详细介绍

英特尔 ISEF 全程指导方案

· 数学 · 物理 · 化学 · 生物 · 计算机 · 工程 ·

学科简介:计算生物与生物信息学 Computational Biology and Bioinformatics

Studies that primarily focus on the discipline and techniques of computer science and mathematics as they relate to biological systems. This includes the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavior, and social systems.

Subcategories:

Computational Biomodeling (MOD): Studies that involve computer simulations of biological systems most commonly with a goal of understanding how cells or organism develop, work collectively and survive.

Computational Epidemiology (EPD): The study of disease frequency and distribution, and risk factors and socioeconomic determinants of health within populations. Such studies may include gathering information to confirm existence of disease outbreaks, developing case definitions and analyzing epidemic data, establishing disease surveillance, and implementing methods of disease prevention and control.

Computational Evolutionary Biology (EVO): A study that applies the discipline and techniques of computer science and mathematics to explore the processes of change in populations of organisms, especially taxonomy, paleontology, ethology, population genetics and ecology.

Computational Neuroscience (NEU): A study that applies the discipline and techniques of computer science and mathematics to understand brain function in terms of the information processing properties of the structures that make up the nervous system.

Computational Pharmacology (PHA): A study that applies the discipline and techniques of computer science and mathematics to predict and analyze the responses to drugs.

Genomics (GEN): The study of the function and structure of genomes using recombinant DNA, sequencing, and bioinformatics.

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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