發(fā)布時(shí)間：2018-05-10 22:15

  本文選題：模糊綜合評(píng)價(jià)法 + BP神經(jīng)網(wǎng)絡(luò)�。� 參考：《河北工業(yè)大學(xué)》2015年碩士論文

【摘要】：水是生命之源,是一切生命生存和發(fā)展不可或缺的重要自然資源,但是由于人們對(duì)水資源保護(hù)意識(shí)不強(qiáng),加之污染物種類隨社會(huì)發(fā)展日趨復(fù)雜,水資源短缺和水質(zhì)污染逐漸成為全球性的重大問題,水環(huán)境的相關(guān)研究也隨之發(fā)展起來(lái)。水質(zhì)評(píng)價(jià)是水環(huán)境研究的一個(gè)重要組成部分,在水資源的管理和維護(hù)中占有重要地位。本文在對(duì)天津市中心城區(qū)景觀河道長(zhǎng)時(shí)間、高密度地采樣監(jiān)測(cè)的基礎(chǔ)上,結(jié)合模糊綜合模型和BP神經(jīng)網(wǎng)絡(luò)理論,依據(jù)天津市中心城區(qū)景觀河道的實(shí)際監(jiān)測(cè)數(shù)據(jù)分析了其主要污染特征,采用優(yōu)化的模糊綜合評(píng)價(jià)法以及基于BP神經(jīng)網(wǎng)絡(luò)的水質(zhì)評(píng)價(jià)方法,對(duì)一級(jí)河道、二級(jí)河道和排水河道的現(xiàn)狀水質(zhì)進(jìn)行了綜合評(píng)價(jià)。并針對(duì)造成水體水質(zhì)現(xiàn)狀的原因進(jìn)行了簡(jiǎn)要的分析。結(jié)果表明:模糊綜合評(píng)價(jià)模型宜采取迭加隸屬度原則;考慮TN指標(biāo)超標(biāo)嚴(yán)重的情況,宜對(duì)含TN因子和不含TN因子的情況分別進(jìn)行評(píng)價(jià);一級(jí)河道、二級(jí)河道7-9月份各指標(biāo)均較差,兩種評(píng)價(jià)結(jié)果均為Ⅴ類,其余月份除TN指標(biāo)外各指標(biāo)情況較好,不含TN因子評(píng)價(jià)結(jié)果均優(yōu)于Ⅳ類;一級(jí)河道、二級(jí)河道水體評(píng)價(jià)結(jié)果為Ⅴ類的比例分別為84.06%和71.74%,優(yōu)于Ⅴ類的比例分別為15.94%和28.26%;排水河道由于其河道的功能原因,水質(zhì)整體超標(biāo)嚴(yán)重。將模糊綜合評(píng)價(jià)法和BP神經(jīng)網(wǎng)絡(luò)水質(zhì)評(píng)價(jià)法進(jìn)行比較。結(jié)果表明:模糊綜合評(píng)價(jià)法和BP神經(jīng)網(wǎng)絡(luò)水質(zhì)評(píng)價(jià)法得到的水質(zhì)評(píng)價(jià)結(jié)果基本一致,二者都考慮了各個(gè)水質(zhì)指標(biāo),都為綜合的水質(zhì)評(píng)價(jià)方法,其中BP神經(jīng)網(wǎng)絡(luò)由于其網(wǎng)絡(luò)的自學(xué)習(xí)性,評(píng)價(jià)結(jié)果更加客觀、準(zhǔn)確,成為水質(zhì)評(píng)價(jià)方法的首選。本研究可以為天津市中心城區(qū)景觀河道的水質(zhì)分析提供理論依據(jù),也可為今后的水體治理和水質(zhì)研究提供一定的數(shù)據(jù)支持以及為其他地區(qū)水體的水質(zhì)分析提供有益的借鑒作用。
[Abstract]:Water is the source of life and an indispensable and important natural resource for the survival and development of all life. However, due to the lack of awareness of water resources protection and the increasing complexity of pollutant types with the development of society, water is the source of life. Water shortage and water pollution have gradually become a major problem in the world, and the research on water environment has also developed. Water quality assessment is an important part of water environment research and plays an important role in the management and maintenance of water resources. On the basis of long time and high density sampling and monitoring of landscape watercourses in downtown Tianjin, this paper combines fuzzy synthesis model and BP neural network theory. Based on the actual monitoring data of landscape river in downtown Tianjin, the main pollution characteristics are analyzed, and the water quality evaluation method based on BP neural network is used to evaluate the water quality of the first class river. The current water quality of the secondary channel and the drainage channel was evaluated comprehensively. The causes of water quality are analyzed briefly. The results show that the fuzzy comprehensive evaluation model should adopt the principle of superposition degree of membership, consider the serious situation of the TN index exceeding the standard, and evaluate the situation with and without TN factor respectively. In July and September, the indexes of secondary river were all worse, and the two kinds of evaluation results were classified into category 鈪，

本文編號(hào)：1871149