2018英特爾ISEF獲獎作品摘要 計算生物與生物信息學 Intel Finalist Abstract Computational Biology and Bioinformatics

獲獎作品基本信息

年份	2018
學科	計算生物與生物信息學 Computational Biology and Bioinformatics
國家/州	United States of America

獲獎作品名稱

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

獲獎作品摘要

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.

---

高中生科研 英特爾 Intel ISEF
資訊 · 課程 · 全程指導
請掃碼添加微信好友

[vc_btn title="聯系電話：(021) 63526628" color="black" align="center" css_animation="fadeIn" link="url:tel%3A02163526628||target:%20_blank|rel:nofollow"]

---

ISEF 簡介

英特爾國際科學與工程大獎賽，簡稱 "ISEF"，由美國 Society for Science and the Public（科學和公共服務協會）主辦，英特爾公司冠名贊助，是全球規模最大、等級最高的中學生的科研科創賽事。ISEF 的學術活動學科包括了所有數學、自然科學、工程的全部領域和部分社會科學。ISEF 素有全球青少年科學學術活動的“世界杯”之美譽，旨在鼓勵學生團隊協作，開拓創新，長期專一深入地研究自己感興趣的課題。

>>> 實用鏈接匯總 <<<

英特爾 ISEF 學術活動詳細介紹

英特爾 ISEF 全程指導方案

· 數學 · 物理 · 化學 · 生物 · 計算機 · 工程 ·

學科簡介：計算生物與生物信息學 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.