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基于多目標(biāo)決策模糊物元法的冷藏車傳感器布點優(yōu)化
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國家自然科學(xué)基金資助項目(31371538)和教育部新世紀(jì)優(yōu)秀人才計劃資助項目(NCET110491)


Optimal Sensor Layout in Refrigerator Car Based on Multi-objective Fuzzy Matter Element Method
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    摘要:

    提出了多目標(biāo)決策模糊物元分析法,,采用中心效果測度方法構(gòu)建模糊物元矩陣,依據(jù)綜合關(guān)聯(lián)度對監(jiān)測點進行優(yōu)選,,實現(xiàn)冷藏車廂內(nèi)傳感器布局的點位優(yōu)化,。結(jié)果表明,,該方法能夠在保證監(jiān)測結(jié)果準(zhǔn)確的前提下,,傳感器數(shù)量從27個減少到7個,,降低了冷鏈運輸成本,。采用統(tǒng)計分析方法和溫度場分析法,,驗證了優(yōu)化后傳感器布局的合理性,。優(yōu)化后傳感器監(jiān)測值具有95%以上的置信水平,優(yōu)化前,、后溫度場分布圖相似率達到90%,,達到冷鏈運輸中既節(jié)約成本又準(zhǔn)確監(jiān)測的雙重要求。

    Abstract:

    Multi-objective fuzzy matter element method was put forward to optimize the sensor quantity. Fuzzy matter element matrix was constructed by means of center effect measure, and the monitoring point was optimized according to the comprehensive correlative degree. Twenty-seven sensors was reduced to 7 in the refrigerator car, which reduced the costs of cold-chain transportation. The statistical analysis method and the temperature field analysis were applied to validate the rationality of the optimization algorithm. The measurement data of sensors had more than 95% of confidence level and the similarity rate of temperature field distribution between before and after optimization reached over 90%, which achieved the dual requirements of cost savings and accurate monitoring in cold chain transportation.

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劉靜,張小栓,肖新清,傅澤田.基于多目標(biāo)決策模糊物元法的冷藏車傳感器布點優(yōu)化[J].農(nóng)業(yè)機械學(xué)報,2014,45(10):214-219. Liu Jing, Zhang Xiaoshuan, Xiao Xinqing, Fu Zetian. Optimal Sensor Layout in Refrigerator Car Based on Multi-objective Fuzzy Matter Element Method[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(10):214-219.

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  • 收稿日期:2014-06-18
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  • 在線發(fā)布日期: 2014-10-10
  • 出版日期: 2014-10-10
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