【文章內(nèi)容簡介】 ded rapidly to the whole world, which imperiled our economic development and people’s living. Therefore, study on its spreading regularity and building the mathematical modeling for predicting and controlling its extension had bee the “Archimedes Heels” for all mathematicians… So, the Logistic regression has been carved in my memory. Two weeks’ training has presented me with a kind of passion and calm thinking much more than just those classical mathematical models. As the patron saint of our humanbeings, the existence of Mathematics and mathematical modeling are maintaining our subsistence and development. Then, when SARS ran riot, when we are suffering from the pain of AIDS, what can I do as a mathematics and mathematical modeling lover who loves life so much?　　懷著這份激情和思考，在大二的秋天，我第一次嘗試了運用數(shù)學建模的知識去解決實際問題，我和另外兩名隊員代表學校參加了全國大學生數(shù)學建模比賽。比賽要求結(jié)合數(shù)據(jù)對長江水質(zhì)做出定量評價，分析各地區(qū)的水質(zhì)污染。并對未來長江水質(zhì)污染發(fā)展趨勢做出預(yù)測分析，制定污水處理計劃。長達17頁的數(shù)據(jù)和多個評價指標對我們來說著實是個挑戰(zhàn)!究竟應(yīng)該選擇哪些數(shù)據(jù)?怎樣綜合考慮多個指標?我們嘗試了近一天，推翻了以前建立的種種模型，有好幾次都被弄得想要放棄，是隊友間的相互鼓勵的力量和鍥而不舍的精神讓我們最終找到了自己滿意的模型：綜合指數(shù)法模型評價長江水質(zhì)，既體現(xiàn)水質(zhì)的各種評價因子，又能反映主要污染物對水質(zhì)的突出作用。通過多元線性回歸擬合預(yù)測未來水質(zhì)污染，建立線性優(yōu)化模型，制定污水處理計劃。我們小組的參賽論文獲北京市二等獎。三天三夜的建模經(jīng)歷，那份澎湃的激情已經(jīng)漸漸平息，取而代之的是更加冷靜的思考：數(shù)學建模創(chuàng)造、創(chuàng)新，成功地解決問題依賴于扎實的數(shù)學基礎(chǔ)知識和過硬的數(shù)學建模能力。依賴于不拘一格的創(chuàng)新思維和創(chuàng)造能力。還依賴于對多方面知識的了解和積累?！　ocketed with this passion and thinking, I tasted to use mathematical modeling into practice and solve the practical problems by attending the National College Mathematical Modeling Contest with the other two schoolmates on behalf of our college. It required us to evaluate the water quality of Changjiang River according to the data, through which we had to analyze the water pollution in every region and predict the trend of it in the future. Finally we had to bring out the plan against it. It was really a challenge for us towards flood of data and estimations as long as 17 pages. We tried almost a whole day only to filter those data and take the evaluations into prehensive account. Pulling down various models we had built before, we were so defeated that we wanted to give up many times. However, we finally found the satisfactory model thanks to our encouragement to each other which armed us with full strength to go managed to evaluate the water quality by Composite index model, which could not only represent the evaluation factors, but also reflect the main impacts of the contaminations to the water pollution. We predicted the future water pollution through multiple linear regressions fitting and brought out the plan against it by building linear optimization model. Finally, we got the second prize in Beijing for our thesis. Three days’ and nights’ modeling experience had cooled our passion and gave us even more calm thinking instead. The creation of the mathematical modeling, along with the successful solution to the problems through it lied on the solid mathematics foundation, strong modeling ability, accumulation of the knowledge on different fields, unique creative ideas and creativity.　　參加數(shù)學建模比賽的經(jīng)歷更加激發(fā)起我的學習興趣，使我在學習數(shù)學理論的同時更加注重它們的應(yīng)用性。除此之外，我抓住一切可能的機會再次參加實際的數(shù)學建模。大三的上學期，我有幸參加了為期3天的電工數(shù)學建模實習：給某大型運動會比賽項目排序。由于對圖論知識很熟悉，我很快將問題轉(zhuǎn)化為尋找最佳Hamilton回路。接近87億種不同的排序的數(shù)據(jù)量，比上次的全國數(shù)模競賽更大，我的算法運行時間相當長而且運行的結(jié)果也很不理想。這種情況的發(fā)生不僅僅沒有打消我的積極性,反而使我的情緒高漲,這是人生中難得的自我考驗,自我提高的機會!通過查詢資料改用遺傳算法，一個數(shù)學模型是否能夠完美地解決實際問題還要考慮其運算成本，實際問題不僅需要一個成功的模型還需要一個快速有效的算法?！　he experience from this contest further aroused my interest in mathematics. I began to pay more attention to its application as well as learning the theories. In addition, I tried to catch every opportunity to take part in the practical mathematical modeling. My efforts finally rewarded when I was in the first term as a junior. I had a chance to participate in the 3day electrician mathematical modeling practiceclassifying the sports programs for a big sports meeting. Being familiar with the Graph Theory, I immediately found the way to solve the problems by seeking the best Hamilton circuit line. Facing the nearly billion data files with different orders much more than that on the National Mathematical Modeling Contest, I spent a long time on Algorithm without any perfect result. I wasn’t defeated towards this case, but so excited instead that I could have such a chance to challenge and improve myself. Looking up dozens of files, I finally made a perfect end of the