<track id="7oo55"><button id="7oo55"></button></track>
    <table id="7oo55"><noscript id="7oo55"></noscript></table>
    <bdo id="7oo55"><th id="7oo55"><form id="7oo55"></form></th></bdo>

  1. 中國高校之窗 設為首頁|添加收藏|聯系我們
    • 北京郵電大學世紀學院通信系科協再出兩篇學生論文被錄用

    中國高校之窗

    96d73512-a536-4413-bc8c-f3fce03c4f67.jpg

    近期,北京郵電大學世紀學院通信與信息工程系科技協會傳來喜訊,繼上次兩名同學的科技論文被錄用后,又有兩名同學的論文被錄用,分別是物聯網創新工作室成員、16物聯網工程專業學生楊蕊銘與王小玄同學所寫的兩篇論文《Modeling and Prediction of New Energy Use》與《基于平均等待時間最小化的電梯自適應調度方案設計》分別被2019 4th International Conference on Energy, Environment and Natural Resources和《創新科技》錄用。

    楊蕊銘,榮獲過北京郵電大學優秀團支書,優秀團員等多項榮譽。在校期間積極參加校內外活動,參與多項學科競賽并積極參加世園會志愿者活動。完成論文《Modeling and Prediction of New Energy Use》并被2019 4th International Conference on Energy, Environment and Natural Resources錄用。其他學生作者:商子彥 楊凱。

    論文簡介如下:

    This paper looks into clean energy consumption in the four states of California (CA), Arizona(AZ), New Mexico(NM) and Texas (TX) by analyzing and comparing the methods of energy consumption, the similarity and difference of their energy composition and the causes for it, and finding out the state with the optimal ways of energy consumption, and based on it, predicts the future energy composition of these states and proposes a target for interstate energy convention. And through multiple regression analysis, and the corresponding indicators of the methods of energy consumption in these states, we compare the ways of new energy consumption in these states, and analyze the difference from the perspective of industries and geographies in these states, which prepares necessary reference for the following modeling. After some basic analysis of the data, we establish a multi-attribute decision making to find a state with optimal composition of energies through the five indicators of energy composition, volume of clean energy consumption etc; and based on the analysis, we find the different characteristics of energy consumption in these states. Then we set up a GM (1,1) model to make prediction based on the data of energy consumption of the near 20 years and project energy consumption of the four states in 2025 and 2050. By means of comparing with different models, we have nearly the same conclusion: CA is a state with optimal energy combination and has best practice for future development. There in projecting the 2025 and 2050 energy consumption, we can use CA as a reference state and set such as the target for energy convention between these four states.

    Key words: Multiple regression analysis, multi-attribute decision making, principal component analysis.

    指導教師:李雷遠、劉剛、任國芳、吳娛、張長江、 張震

    王小玄,擔任班級團支書職務,榮獲過優秀團員、校級獎學金等多項榮譽。在校期間積極參加校內外活動,創新競賽及世園會志愿者活動。

    期刊名稱:《創新科技》

    指導教師:李雷遠、劉剛、任國芳、吳娛

    論文名稱:《基于平均等待時間最小化的電梯自適應調度方案設計》

    簡介:在電梯群控系統中,由于存在著很多的不確定性因素,如乘客數量的未知,廳層召喚的未知性和隨機性,使得電梯群控成為一個具有非線性和不確定性的復雜的多目標決策問題。本文將模糊推理和神經網絡相結合來處理非線性、隨機性和模糊性等問題。根據專家規則確定了進行優化調度的模糊神經網絡,采用誤差反向傳播算法對網絡進行學習。模糊神經網絡融合了模糊邏輯和人工神經網絡的優點,易于表達知識并且有自學習能力。將平均候梯時間、平均乘梯時間、擁擠度和能耗等作為參考評價指標,建立了多目標優化的電梯群控系統的數學模型。用Matlab對實際呼梯信號進行調度仿真,驗證了算法的有效性。

    關鍵詞:模糊神經網絡;電梯群控;多目標規劃;模糊規則

    (通訊員:李是堯)

    中國高校之窗

    ?
    關于我們 | 聯系我們 | 網站導航

    中國教育電視臺特約合作網站
    中國高校之窗  京ICP備12005367號 

    版權所有 Copyright 2005-2025 All Rights Rreserved

    草民电影