2017年深圳杯建模挑战赛C题决赛论文（独家）
本人2017年入选了深圳杯建模决赛，这是正式答辩时的论文。仅供各位建模的同学学习参考。基于问趣二中的预测结果,计算得出未来十年的总成本数量及各模式下各分项成本(涵盖直接业务成本、经济技术成本、问接的当下和远期社会成本)比例,分析其变化趋势,并通过作图直观反映。考虑到目前深圳已经开始建立生活垃吸强制分类制度,本文详细分析了家庭分类与专业分类两种前端分流模式对总成本的影响。问题三的分析基于较为完善的模型,对远期效益成木比进行估算,从深圳市具休情况岀发,设计一套生活垃圾处理的优选模式,以供参考。符号说明变量含义生活垃圾处理社会总成本直接成本直接业务成本收集成本第种收集方式的成本第种收集方式中的第种成本运输成木第种运输方式的成本第种运输方式中的第种成本处理成本第种处理方式成本绎济技术成本固定成本第种固定成本可变成本第种可变成本税收减免第种税收减免间接的当下和远期社会成本,即环境损失成本第种环境损失成本年度垃圾处理量湿垃圾占垃圾总量的比例垃圾分类中的干垃圾总量垃圾分类中的湿垃圾总量模型假设假设在估算时间内国家及深圳市相关政策不变。假设在估算时间内折现※为假设在佔算时间内政府对源头分类的补贴保持不变倀设在估算时间内填埋、焚烧、生物处理三种方式下的基准地价的季度增长率分别为模型建立与求解问题一的模型建立模型的准备针对问题一,将生活垃圾处理的社会总成本分为直接业务成本、经济技术成本、问接的当下和远期社会成本,如图生活垃圾处理社会总成本直接业务成本D经济技术成本E间接的当下和远期社会成本图生活垃圾处理社会总成本构成直接业务成本分析在直接业务成木中,我们又将其细化分成了垃圾收集成木、运输成木和处理成本三个部分,如图直接业务成本D收集成本D处理成本D匚运输成本D图直接业务成本构成4()收集成本分析由附件一可知,在不同的垃圾处理模式中,收集方式分别对应混合收集、源头分类收集和混合收集末端分类。即收集成本可划分为混合收集成本源头分类收集成本及混合收集木端分类成本而且每一种收集方式的成本又涵盖了公用垃圾桶成本(分别对应)和运输成本(分别对应),值得注意的是,源头分类收集方式会有额外的政府补贴,而混合收集末端分类方式在末端分类时会占用额外的土地、人力、设备等,因此会产生额外的成本和,如图收集成本De混合收集源头分类成本收集成本集,末端分类成本D公用福政府Dcg成本图收集成本构成()运输成本分析运输成本分为混合运输成本和分类运输成本两类,其中每一种运输成本都包括转运站成本(表示从各公用桶运输到转运站进行进一步处理所需成本,分别对应)和运输成本(分别对应),如图:运输成本Dt混合分类运输运输成本成本转运站成运输站成运输本成本DtD图运输成本构成5()处理成本分析由于处理模式的不同,处理成本可分为焚烧处理成本、填埋处理成本以及生物处理成本,如图处理成本D。焚烧填埋生物处理处理处理成本成本成本DstD图处理成本构成经济技术成本分析经济技术成本包括固定成本、可变成本和税收减免。固定成本分为土地成本和建设成本可变成本包括飞灰补贴、底灰补贴电价补贴、渗沥液补贴以及其他补贴;税收减笕分为増值税减笕、营业税减免和企业所得税减免,如图:经济技术成本E税收减免可变成本定成本E稅减税减税减其他补赎二c5EC2填埋场生物处理厂图经济技术成本构成间接的当下和远期社会成本分析问接的当下和远期成本涵盖了由于环保标准提高所花费的成本、水污染造成的损失、大气污染造成的损失以及固体废弁物污染造成的损失如图6问接的当下和远期社会成本L水污染损失气污染固体废物污染损失L4业损幻1匚人体健康损失[林损头「其他损类图间接的当下和远期社会成本构成模型的建立考虑到不同情况下,决策者会选择不同的模式组合方式。因此,在计算社会总成本时,本文选用各个模式下不同环节所需成本的叠加,从而求得深圳市生活垃圾处理的社会总成木。直接业务成本的计算直接业务成本包括收集成本、运输成本、处理成本直接业务成本的计算公式为:()收集成本的计算公式为=∑∑++代表混合收集成本,代表源头分类收集成本,代表源头混合收集,末端分类成木;代表第种收集方式的公用桶成木,代表第种收集方式的运输成本,代表单位垃圾消耗的公用桶成本,代表生活垃圾年产量,此成本仅包括垃圾桶至小型转运站的成本,如果决策者选择源头混合收集,末端分类方式收集垃圾,则应该加上额外的土地、设各、人工等成本(后面统称为额外成本),如果选择源头分类,则应加上政府补贴;代表单位吨数单位公里运输价格(是一个与距离有关的分段函数),代表距离;代表单位湿垃圾政府补贴成木;代表单位土地、设备、人工等的成木代表湿垃圾占总垃圾量的比重。()运输成本包括混合运输成本、分类运输成本运输成本的计算公式为7代表第种运输方式的转运站成本,包括转运站人工费,以及设备维护费等,代表第科运输方式的运输成本,此成本仅包括小型转运站至末端垃圾处理站的成本,代表单位转运站成本。()处理成本包括焚烧成本、填埋成本和生物处理成本处理成木的计算公式为代表单位垃圾焚烧处理成本;代表单位垃圾填埋处理成木;代表单位垃圾生物处理成本。经济技术成本的计算经济技术成本包括固定成本、可变成本、税收减免经济技术成木的计算公式为固定成本包括焚烧垃圾的十地成本、填埋的十地成本、建设成木。固定成木的计算公式为:代表当年地价,代表十地面积,代表折现率,代表工业用地年;十地机会成本为;代表年地价,代表季度地价增长率,代表时间:代表填哩高度;ρ代表填埋密度代表十地机会成本;代表建设补贴。可变成本包括飞灰补贴、底灰补贴、电价补贴渗沥液补可变成本的计算公式为8=代表单位底灰处理补贴,代表底灰量,代表单位飞灰处理补贴,代表K灰量;代表上网电价补贴,代表超额供电补贴;代表单位污水处理补贴,代表污水处理量税收减免包括增值税减免、营业税减免企业所得税减免税收减免的计算公式为:间接的当下和远期社会成本的计算间接的当下和远期社会成本包括环保标准提高后所需成本(远期环境标准提髙后垃圾处理费升高所需成本)、水污染导致的健康损失、空气污染健康损失、固体废弃物污染损失。水污染导致的健康损失包括早逝引起的健康损失、疾病治疗费用和误工损失;由于垃圾厂排放的气休中对人体造成巨大损失的气体为二嵁英,故将空气污染健康损失考虑为二嗯英造成的健康损失;在计算固休废弃物污染时,采用市场价值法对生活垃圾固休废弃物造成的人工管理费、设备费和运输费等费用进行计算不管对生活垃圾使用哪种处理方式,在计算生活垃圾堆存造成的经济损失时,以需按填埋量来进行计算间接的当下和远期社会成本为:∑∑总数总数指标评价和危险特征阐述,结合国际组织的研究成果,对水污染健康损伤的不良影响进行定量评{,代表年人均收入,代表就诊人数,代表人均治疗费用,代表日均收入,代表住院病例,代表每患病者入住天数;代表不同浓度区域的编码,代表不同浓度区域的二惡英致癌风险代表每平方公里人口密度,代表不同浓度区域所占的面积,代表个体生命价值代表治疗费用;代表生活垃圾堆存损失系数,代表生活垃圾堆存量。综上,由上述各式可得生活垃圾的社会总成本为:+十问题二模型建立及解决各模式的直接成本估算方案完善深圳市生活垃圾直接成木包括直接业务成木和经济技术成木,由式()至式()可知,城市生活垃圾直接成本为:当期社会总成本估算由已知数据代入问题一模型中可知年的社会总成本为:+十元日前仅得到年深圳市生活垃圾年产量数据,如图:s0047544069406图年深圳市生活垃圾年产量无法直接计算出当期以及未来十年各模式下直接成本,故基于灰色预测方法,根捃此数据,估算得出年的生活垃圾年产量如表
- 2020-12-05下载
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Key Technologies for 5G Wireless Systems
5G无线通信系统关键技术（剑桥大学出版社） 2017年出版 对于5G所有最新技术进行了详细说明 很全的工具书Key Technologies for5G Wireless SystemsVINCENT W. S, WONGUniversity of British ColumbiaROBERT SCHOBERUniversity of Erlangen-NurembergDERRICK WING KWAN NGUniversity of New South WalesLI-CHUN WANGNational Chiao-Tung University即CAMBRIDGEUNIVERSITY PRESSCAMBRIDGEUNIVERSITY PRESSUniversity Printing House. Cambridge CB2 SBS. United KindomOne Liberty Plaza, 20h Floor New York, NY I(H0X, USA477 williamstown Road, port Melbourne, yic 3207 australia48424, 2nd Floor, Ansar Rod, Daryaganj. Delhi- I l4XH2, India79 Anson Road, #o6-(/ 00, Singapore 079%MCambridge University Press is part of the Lniversity of CambridgeIt furthers the University s mission by disseminating knowledge in the pursuit ofeducation, leaming and research at the highest international levels of excellence.www.cermbrid吧eInformtiononthistitlewww.cambridgeorg/978110713241810,1017③781316771655C Cambridge University Press 2017This puhlication is in copyright. Subjcct to sututonry exceptionand to the provisions of relewant collective licensing agreementsno reproduction of any part may take place without the writtenpermission of Cutmbridgre University Press.First published 2(117Printed in the United Kingdom by TJ International Ltd. Padstow, CornwallA catalogue recor for this pudlieafiove is aailable fromm the British LibraryLibrary of Congress Cataloging- in Pi hlicaiomz dataNames: Wong, Vincent W.S., editorTitle: Key technologies for 5G wireless systems/edited by Vincent W.S. Wong [and 3 otherOther titles key technologies for five g wireless svstemsDescription: Carmbrisige: New York, NY: Cambridge Lniversity Press, 2017.Identifiers: l CCN 2016045220)1 ISBN 9781 172418 (hardback)Subjects: LCSH: Wireless communication systems, I Machine-to-machinecommunications. Internet of things.Classitication: LCC TKs1032K49 2(17 DDC 621.38450-dc23LcrecordavailaBleathttps://lccnioc-gov/2016m5220)ISBN 978-1-107-17241- HardbackCambridge University Press has no responsibility for the persistence or accuracy ofURLs for extermal or third-party Internet websites referred to in this puhlication,and does not guarantee that any content on such websites is, or will remainaccurate of appropriateContentsList of Contributorspage xvIPrefaceKXIOverview of New Technolog ies for 5G SystemsVincent W S, Wong, Robert Schober, Derrick Wing Kwan Ng, and Li-Chun Wang1.1 Introduction1.2 Cloud Radio Access Networks1.3 Cloud Computing and Fog Computing1. 4 Non-orthogonal Multiple Access1. 5 Flexible Physical Layer Design334.4671. 6 Massive MIMo1. 7 Full-Duplex Communications1. 8 Millimeter wave1.9 Mobile Data Offloading, LTE-Unlicensed, and Smart Data Pricing131. 10 IoT M2M. and D2D1. I1 Radio Resource Management, Interference Mitigation, and Caching61. 12 Energy Harvesting Communications1. 13 Visible Light Communication19Acknowledgments20ReferencesPart I Communication Network Architectures for 5G Systems25Cloud Radio Access Networks for 5G Systems27Chih-Lin I, Jinn Huang, Xueyan Husang, Rongwved Ren, and Yami. Chen2.1 Rethinking the Fundamentals for 5G Systems272 User- Centric Networks2923 C-RAN Basics292.3.1 C-RAN Challenges Toward SGI302.4 Next Generation Fronthaul Interface (NGFI: The FH Solutionfor SGC-RAN312. 4.1 Proof-of-Concept Development of NGFI33Contents2.5 Proof-of-Concept Verification of Virtualized C-RAN2.5.1 Data packets3725.2 Test Procedure382.5.3 Test Results392. 6 Rethinking the Protocol Stack for C-RAN2.6.1 Motivation402.6.2 Multilevel Centralized and Distributed Protocol Stack402.7 Conclusion45AcknowledgmentsReferencesFronthaul-Aware Design for Cloud Radio Access Networks48Liang Liu, Wei Yu, and Osvaldo Simeone3. 1 Introduction483.2 Fronthaul-Aware Cooperative Transmission and Reception493. 2.1 Uplink513.2.2 Downlink573.3 Fronthaul-Aware Data Link and Physical layers61.3. I Uplink633.3.2 Downlink693.4 Conclusion73Acknowledgments74References74MobEdge computing76Ben Liang4.1 Introduction764.2 Mobile Edge Computing774.3 Reference architecture794.4 Benefits and Application Scenarios804 4.1 User-Oriented Use cases4. 4.2 Operator-Oriented Use Ca814 5 Research challenges824.5.1 Computation Offloading824.5.2 Communication Access to Computational Resources834.5.3 Multi-resource Schedulin844.5 4 Mobility Management854.5.5 Resource Allocation and Pricing4.5.6 Network functions virtualization864.5, 7 Security and Pri864.5.8 Integration with Emerging Technologies874.6 Conclusion88ReferencesContentsDecentralized Radio Resource Management for Dense HeterogeneousWireless networksAbolfazl Mehhodniya and Fumiyuki Adach5.1 Introduction925.2 System Model935.2.1 SINR Expression5.2.2 Load and Cost Function Expressions955.3 Joint BSCSA/UECSA ON/OFF Switching Scheme965.3.1 StrateTy Selection and Beacon Transmission53.2 UE AssocIation5.3.3 Proposed Channel Segregation Algorithms985.3.4 Mixed-Strategy Update3.4 Computer Simulation5.5 Conclusion104Acknowledgments04References105Part ll Physical Layer Communication Techniques107Non-Orthogonal Multiple Access(NOMA)for 5G Systems109Wei Llang, Zhiguo Ding, and H. Vincent Poor6.1 Introduction1106.2 NOMA in Single-Input Single-Output(SISO)Systems1126.2.1 The basics of nomaI126. 2. 2 Impact of User Pairing on NOMA136.2,3 Cognitive Radio Inspired NOMA6. 3 NOMA in MIMO Systems1206.3.1 System Model for MIMO-NOMA Schemes1216.3.2 Design of Precoding and Detection Matrices with Limited CSIT 1236.3.3 Design of Precoding and Detection Matrices with Perfect CSIT 1266.4 Summary and Future Directions128ReferencesFlexible Physical Layer Design133Maximilian Matthe, Martin Danneberg, Dan Zhang, and Gerhard Fettweis7.1 Introduction1337. 2 Generalized Frequency Division Multiplexing357.3 Software-Defined waveform1377. 3. 1 Time Domain Processing1387.3.2 Implementation Architecture1387.4 GFDM Receiver Design14174 Synchronization unit1427. 4.2 Channel Estimation Unit1474.3 MIMo-GFDM Detection Unit145Contents7.5 Summary and Outlook147Acknowledgments148References488Distributed Massive MIMO in Cellular Networks15IMichail Matthaiou and Shi Jin8. I Introduction15l8. 2 Massive MIMO: Basic Principles1528.2.1 Uplink Downlink Channel Models1538.2.2Favorable Propagation1548.3 Performance of Linear Receivers in a Massive MIMO Uplink1548.4 performance of linear precoders in a massive mimo downlink1578. s Channel estimation in massive mimo systems1588.5.1 Uplink Transmission1598.5.2 Downlink Transmission1608.6 Applications of Massive MIMO Technology1618.6.1 Full-Duplex Relaying with Massive Antenna Arrays1618.6.2 Joint Wireless Information Transfer and Energy Transfer forDistributed massive mimo1638.7 Open Future Research Directions1678. 8 Conclusionl68References169Full-Duplex Protocol Design for 5G Networks172Tanelf Ahonen and Risto wichman9.1 Introduction1729. 2 Basics of Full-Duplex Systems1739.2.1 In-Band Full-Duplex Operation Mode1739.2.2 Self-Interference and Co-channel Interference1749.2.3 Full-Duplex Transceivers in Communication Links1759. 2. 4 Other Applications of Full-Duplex Transceivers1789.3 Design of Full-Duplex Protocols1799.3, 1 Challenges and Opportunities in Full-Duplex Operation1799.3.2 Full-Duplex Communication Scenarios in 5G NetworksR9.4 Analysis of Full-Duplex Protocols1829.4.1 Operation Modes in Wideband Fading Channels1829. 4, 2 Full- Duplex Versus Half-Duplex in Wideband Transmission1849.5 Conclusion1849.5.1 Prospective Scientific Research DirectionsI849.5.2 Full-Duplex in Commercial 5G Networks185RLItrtncekl8610Millimeter Wave Communications for 5G Networks188Jiho Song, Miguel R Castellanos, and David J. LoweContentsⅸx10.1 Motivations and Opportunities18810.2 Millimeter Wave Radio Propagation18910. 2.1 Radio Attenuation1890. 2. 2. Free-Space Path LOSs19I10.2.3 Severe shadow19310.2 4 Millimeter Wave Channel model19310.2.5 Link Budget Analysis19410.3 Beamforming Architectures19510.3, Analog beamforming solutions19610.3.2 Hybrid Beamforming Solutions20010.3.3 Low-Resolution Receiver Architecture2010.4 Channel Acquisition Techniques20110.4.1 Subspace Sampling for Beam Alignment20210.4.2 Compressed Channel estimation Techniques20510.5 Deployment Challenges and Applications20710.5.1 EM Exposure at Millimeter Wave Frequencies20710.5.2 Heterogeneous and Small-Cell Networks208Acknowledgments209References209Interference Mitigation Techniques for Wireless Networks214Koralia N Pappi and George K, Karag annidis1 1.1 Introduction21411.2 The Interference Management Challenge in the 5G vision21411. 2. 1 The 5G Primary Goals and Their Impact on Interference2141 1.2.2 Enabling Technologies for Improving Network Efficiencyand Mitigating Interference21611.3 Improving the Cell-Edge User Experience: Coordinated Multipoint218I 1.3.1 Deployment Scenarios and Network Architecture2181 13. 2 CoMP Techniques for the Uplink22011.3.3 CoMP Techniques for the Downlink2211 1.4 Interference Alignment: Exploiting Signal Space Dimensions2231 1.4.1 The Concept of Linear Interference Alignment224L1. 4.2 The Example of the X-Channel225I 1. 4.3 The K-User Interference Channel and Cellular NetworksAsymptotic Interference Alignment22611.4.4 Cooperative Interferenee Networks22711.4.5 Insight from IA into the Capacity Limits of Wireless Networks 22711.5 Compute-and-Forward Protocol: Cooperation at the ReceiverSide for the Uplink22811.5.1 Encoding and Decoding of the CoF Protocol22811.5.2 Achievable-Rate Region and Integer Equation Selection23011.5.3 Advantages and Challenges of the CoF Protocol232IL6 Conclusion233References233
- 2020-12-06下载
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