發(fā)布時(shí)間：2017-12-31 01:05

  本文關(guān)鍵詞：基于貝葉斯網(wǎng)絡(luò)的施工項(xiàng)目成本動(dòng)態(tài)預(yù)測(cè)方法研究　出處：《昆明理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 施工項(xiàng)目成本 ISM模型 貝葉斯網(wǎng)絡(luò) 動(dòng)態(tài)預(yù)測(cè)

【摘要】：隨著國民經(jīng)濟(jì)快速發(fā)展,建筑施工行業(yè)進(jìn)入了跨越式發(fā)展的新時(shí)代,國內(nèi)外大量建筑施工企業(yè)加入到市場化競爭。建筑施工行業(yè)面對(duì)復(fù)雜多變的市場環(huán)境,競爭激烈、利潤低薄,生存壓力巨大,因此大多數(shù)建筑施工企業(yè)將管理的重點(diǎn)放在成本管理工作上。而建筑施工企業(yè)成本管理首當(dāng)其沖的工作是成本預(yù)測(cè),它是施工項(xiàng)目編制成本計(jì)劃、實(shí)施成本管控的首要環(huán)節(jié),同時(shí)也是施工企業(yè)投標(biāo)階段進(jìn)行項(xiàng)目決策的主要依據(jù),對(duì)于提升和改善施工企業(yè)的生存發(fā)展能力以及市場競爭能力,具有舉足輕重的影響力。目前國內(nèi)外成本預(yù)測(cè)的方法主要存在以下問題：(1)部分施工企業(yè)項(xiàng)目成本意識(shí)淡薄,未形成系統(tǒng)的成本管理體系。(2)成本預(yù)測(cè)方法落后,成本管理水平偏低。(3)片面對(duì)待成本管理,在成本預(yù)測(cè)過程中忽視了質(zhì)量、工期、安全及標(biāo)準(zhǔn)化建設(shè)與成本之間的對(duì)立統(tǒng)一關(guān)系。 國內(nèi)外學(xué)者采用神經(jīng)網(wǎng)絡(luò)方法、灰色理論、掙值分析法、模糊理論、遺傳算法、影響因素分析、工程量清單計(jì)價(jià)分析、多元線性回歸法、地質(zhì)預(yù)測(cè)方法、貝葉斯網(wǎng)絡(luò)和傳統(tǒng)風(fēng)險(xiǎn)評(píng)估法等多種模型和方法進(jìn)行了施工項(xiàng)目成本的預(yù)測(cè)及研究,開展施工項(xiàng)目成本預(yù)測(cè)的多方面探索,獲得了很大成效,但這些方法仍然存在以下幾個(gè)方面的缺陷：(1)以往的研究均只能實(shí)現(xiàn)對(duì)施工項(xiàng)目成本的靜態(tài)預(yù)測(cè),而不能實(shí)現(xiàn)任意時(shí)點(diǎn)施工成本的動(dòng)態(tài)預(yù)測(cè)；因此,這些成本預(yù)測(cè)方法的應(yīng)用被局限在施工投標(biāo)階段,而不能全面應(yīng)用于指導(dǎo)施工項(xiàng)目成本風(fēng)險(xiǎn)的動(dòng)態(tài)控制。(2)研究的方法大部分沒有考慮成本的形成過程多個(gè)影響因素之間復(fù)雜的交互作用關(guān)系,以及這種復(fù)雜關(guān)系影響最終施工項(xiàng)目成本的機(jī)理；因此很難用于指導(dǎo)和改善成本控制過程。 本文將ISM方法與貝葉斯網(wǎng)絡(luò)相結(jié)合,分析研究施工項(xiàng)目成本影響因素,確定各影響因素對(duì)造價(jià)構(gòu)成分項(xiàng)的影響程度和相互關(guān)系,建立ISM解釋結(jié)構(gòu)模型,基于ISM模型進(jìn)行貝葉斯網(wǎng)絡(luò)分析預(yù)測(cè),構(gòu)建了施工項(xiàng)目的成本動(dòng)態(tài)預(yù)測(cè)模型,并通過工程案例對(duì)該模型進(jìn)行了驗(yàn)證。本文的研究主要有以下優(yōu)勢(shì)和成果： (1)基于貝葉斯網(wǎng)絡(luò)的施工項(xiàng)目成本預(yù)測(cè)方法思路清晰,方法簡便,在實(shí)際工作中也很容易操作,反映出來的結(jié)果與實(shí)際情況吻合度良好,可靠性較高,而且能夠即時(shí)動(dòng)態(tài)預(yù)測(cè)項(xiàng)目實(shí)施過程中的特定成本,因此,在施工項(xiàng)目成本管理領(lǐng)域具有較好的應(yīng)用前景。 (2)通過基于貝葉斯網(wǎng)絡(luò)的施工項(xiàng)目成本預(yù)測(cè)模型的正向分析可以迅速求解項(xiàng)目的預(yù)期成本,而通過貝葉斯網(wǎng)絡(luò)模型的反向分析可以迅速求出項(xiàng)目成本風(fēng)險(xiǎn)的致險(xiǎn)因子,以此為依據(jù)可以實(shí)現(xiàn)施工項(xiàng)目成本的動(dòng)態(tài)預(yù)警,并未項(xiàng)目的成本管理與成本控制提供有效的指導(dǎo)。
[Abstract]:With the rapid development of the national economy, the construction industry has entered a new era of leapfrog development, a large number of domestic and foreign construction enterprises to join the market competition. The construction industry faced with complex market environment, fierce competition, low profits thin, great pressure to survive, so most of the construction enterprise management will focus on cost management work. The construction enterprise cost management work is the cost forecast, it is the preparation of construction project cost plan, the primary aspects of the implementation of cost control, but also the main basis for construction project decision-making enterprises bidding stage, to enhance and improve the construction enterprise's survival and development ability and market competition ability, has a great influence methods at home and abroad. The cost of the forecast mainly has the following problems: (1) part of the construction enterprise project cost consciousness (2) the cost prediction method is lagging behind and the cost management level is low. (3) one-sided cost management is neglected in the cost prediction process, which ignores the unity of opposites between quality and duration, safety and standardization construction and cost.
Scholars at home and abroad by using neural network method, grey theory, earned value analysis method, fuzzy theory, genetic algorithm, factor analysis, BOQ valuation analysis, multiple linear regression method, geological prediction method, Bayesian network and traditional risk assessment method of various models and methods of prediction and research of the construction project cost, explore in many ways to carry out the prediction of construction project cost, achieved great results, but these methods still exist defects in the following aspects: (1) previous studies were only used to predict the static state of the construction project cost, and can not achieve dynamic prediction at any time point for the construction cost; therefore, the application of prediction method of these costs is limited in the construction bidding stage, dynamic control and not fully applied to guide the construction project cost risk. (2) research methods most did not test the formation process of considering cost It is difficult to guide and improve the cost control process due to the complex interaction between multiple factors and the mechanism of the complex relationship affecting the final construction project cost.
In this paper, the ISM method and Bias network combined with the analysis of the influencing factors of the construction project cost, to determine the influence factors and the relationship between the degree of breakdown of the cost, the establishment of ISM structural model, Bias network analysis and prediction based on ISM model, the construction cost of construction project dynamic prediction model, and the model was verified by the case study. This research mainly has the following advantages and achievements:
(1) Bayesian network construction project cost forecast method based on clear thinking, the method is simple, in practice is also very easy to operate, reflected the results agree with the actual condition of good, high reliability, but also the specific cost, real-time dynamic prediction in the process of project implementation, therefore, has a good application prospect in the field of cost the management of construction projects.
(2) can be expected to quickly solve the project cost through positive analysis prediction model based on Bayesian network construction project cost, and the reverse of the Bayesian network model analysis quicklysolute project cost risk risk factors, on this basis can realize dynamic early warning construction project cost, cost management and cost of the project is not to provide effective guidance.

【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TU723.3

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