本文關(guān)鍵詞：基于蟻群-粒子群混合算法的水資源優(yōu)化配置研究　出處：《西北農(nóng)林科技大學(xué)學(xué)報(bào)(自然科學(xué)版)》2015年01期 　論文類(lèi)型：期刊論文

  更多相關(guān)文章： 水資源 優(yōu)化配置 蟻群-粒子群混合算法 渭北工業(yè)區(qū)

【摘要】：【目的】對(duì)區(qū)域水資源的合理優(yōu)化配置進(jìn)行研究,為區(qū)域經(jīng)濟(jì)的發(fā)展、水資源的合理開(kāi)發(fā)利用和節(jié)水型社會(huì)的建立提供參考。【方法】建立以經(jīng)濟(jì)、社會(huì)、生態(tài)環(huán)境效益為目標(biāo)函數(shù),各目標(biāo)加權(quán)和為最優(yōu)解的水資源優(yōu)化配置模型,采用蟻群-粒子群混合算法對(duì)模型進(jìn)行求解,并對(duì)渭北工業(yè)區(qū)進(jìn)行水資源優(yōu)化配置的實(shí)例分析,通過(guò)原供水量與優(yōu)化配置水量的比較驗(yàn)證所建立模型的合理性�！窘Y(jié)果】經(jīng)計(jì)算,75%保證率下渭北工業(yè)區(qū)水資源的配置結(jié)果為:2015年地表水、地下水、外調(diào)水、中水供水量分別為1 747.30,13 244.84,12 905.95和1 060.23萬(wàn)m3;2020年各水源供水量分別為2 019.19,12 214.42,23 530.42和1 798.60萬(wàn)m3;與原始供水量相比,2015年和2020年總供水量分別減少312.73和421.11萬(wàn)m3,表現(xiàn)在農(nóng)業(yè)供水量減少,生活、工業(yè)、生態(tài)用水均達(dá)到供需平衡�！窘Y(jié)論】基于蟻群-粒子群混合算法的水資源優(yōu)化配置結(jié)果合理,可作為研究區(qū)水資源合理開(kāi)發(fā)利用決策的參考;蟻群-粒子群混合算法收斂速度快,尋優(yōu)性能優(yōu)越,可用于水資源優(yōu)化配置的分析。
[Abstract]:[Objective] to study the optimal allocation of regional water resources, for the development of regional economy, reasonable exploitation and utilization of water resources and water-saving society provides the reference for the establishment. [method] to establish economic, social, ecological and environmental benefit as the objective function, the target weight and optimal allocation of water resources is the optimal solution of the model, the ant colony particle swarm algorithm to solve the model, and the Weibei industrial zone for example analysis of the optimal allocation of water resources, by comparing the original verification water supply and optimal allocation of water to the rationality of the model. [result] after calculation, 75% guarantee rates in Weibei industrial zone of water resources allocation results 2015: surface water, groundwater, water transfer, water supply was 1 747.30,13 905.95 244.84,12 and 10 million 602 thousand and 300 m3; the water supply in 2020 is 2 019.19,12 214.42,23 530.42 and 1798.6 respectively. 0 000 m3; compared with the original water supply, the total water supply in 2015 and 2020 respectively by 312.73 and 4 million 211 thousand and 100 m3, in the agricultural water supply to reduce the amount of life, industry, ecological water reached the balance of supply and demand. [Conclusion] Based on ant colony particle swarm algorithm for the optimal allocation of water resources is reasonable, can be used as water resources research in the rational development and utilization of reference for decision making; ant colony particle swarm optimization algorithm has a fast convergence speed, superior performance, can be used for the analysis of optimal allocation of water resources.

【作者單位】： 西安理工大學(xué)水利水電學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(51079120,51209170) 陜西省教育廳2010年省級(jí)重點(diǎn)實(shí)驗(yàn)室項(xiàng)目(2010JS077)
【分類(lèi)號(hào)】：TV213.4
【正文快照】： 隨著人口的增長(zhǎng)及社會(huì)經(jīng)濟(jì)的發(fā)展,區(qū)域需水量不斷增加,水資源供需矛盾日益突出,水資源短缺已由區(qū)域性問(wèn)題逐步惡化成為全球性問(wèn)題[1],水將成為21世紀(jì)可持續(xù)發(fā)展的嚴(yán)重制約因素。因此,水資源已不僅僅是人類(lèi)生存的基礎(chǔ)性資源,也是人類(lèi)生存的戰(zhàn)略性資源。為了緩解水資源缺乏給人

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本文編號(hào)：1429639