Dynamic Identification and Evolution of Urban-suburban-rural Transition Zones Based on the Blender of Natural and Humanistic Factors: A Case Study of Chengdu, China

Urban-suburban-rural(U-S-R)zones exhibit distinctive transitional characteristics in interaction between human and nature.U-S-R transition zones(U-S-RTZ)are also highlighting the function diversity and landscape heterogeneity across territorial spaces.As a super megacity in western China,Chengdu’s rapid urbanization has driven the evolution of U-S-R spaces,resulting in a sequential structure.To promote the high-quality spatial development of urban-rural region in a structured and efficient manner,it is essential to con-duct a scientific examination of the multidimensional interconnection within the U-S-RTZ framework.By proposing a novel identifica-tion method of U-S-RTZ and taking Chengdu,China as a case study,grounded in a blender of natural and humanistic factors,this study quantitatively delineated and explored the spatial evolutions of U-S-RTZ and stated the optimization orientation and sustainable devel-opment strategies of the production-living-ecological spaces along the U-S-R gradients.The results show that:1)it is suitable for the quantitative analysis of U-S-RTZ by established three-dimensional identification system in this study.2)In 1990-2020,the urban-sub-urban transition zones(U-STZ)in Chengdu have continuously undergone a substantial increase,and the scale of the suburban-rural transition zones(S-RTZ)has continued to expand slightly,while the space of rural-ecological transition zones(R-ETZ)has noticeably compressed.3)The landuse dynamics within U-S-RTZ has gradually increased in 1990-2020.The main direction of landuse transition was from farmland to construction land or woodlands,with the expansion of construction land being the most significant.4)R-ETZ primarily focus on ecological functions,and there is a trade-off relationship between the production-ecological function within the S-RTZ,and in the U-STZ,production-living composite functions are prioritized.This study emphasizes the importance of elastic planning and precise governance within the U-S-RTZ in a rapid urbanization region,particularly highlighting the role of suburbs as landscape corridors and service hubs in urban-rural integration.It elucidates to the practical implications for achieving high-quality development of integrated U-S-R territorial spaces.

Identification and Evaluation of Low Resistivity Pay Zones by Well Logs and the Petrophysical Research in China

This paper presents an overview of petrophysical research and exploration achievements of low resistivity pay （LRP） zone by well logs in China. It includes geological characteristics and characteristics of well log response of the low resistivity pay zones discovered and evaluated in recent years, as well as the problems in recognizing and evaluating low resistivity pay zones by well logs. The research areas mainly include the Neogene formations in the Bohai Bay Basin, the Triassic formations in the northern Tarim Basin and the Cretaceous formations in the Junggar Basin, The petrophysical research concerning recognition and evaluation of the low resistivity pays, based on their genetic types, is introduced in this paper.

A new methodology for identification of potential pay zones from well logs: Intelligent system establishment and application in the Eastern Junggar Basin, China

In recent years, as the exploration practices extend into more complicated formations, conventional well log interpretation has often shown its inaccuracy and limitations in identifying hydrocarbons. The Permian Wutonggou Formation hosts typical clastic reservoirs in the Eastern Junggar Basin. The sophisticated lithology characteristics cause complex pore structures and fluid properties. These all finally cause low well testing agreement rate using conventional methods. Eleven years＇ recent statistics show that 12 out of 15 water layers have been incorrectly identified as being oil or oil/water layers by conventional well log interpretation. This paper proposes a methodology called intelligent prediction and identification system （IPIS）. Firstly, parameters reflecting lithological, petrophysical and electrical responses which are greatly related to reservoir fluids have been selected carefully. They are shale content （Vsh）, numbered rock type （RN）, porosity （φ）, permeability （K）, true resistivity （RT） and spontaneous-potential （SP）. Secondly, Vsh, φ and K are predicted from well logs through artificial neural networks （ANNs）. Finally, all the six parameters are input into a neuro-fuzzy inference machine （NFIM） to get fluids identification results. Eighteen new layers of 145.3 m effective thickness were examined by IPIS. There is full agreement with well testing results. This shows the system＇s accuracy and effectiveness.

Newly-generated Seismic Rupture Zone:Identification,Type Division and Seismogeological Significance

The results of geological research show that those phenomena such as surface geology,geomorphology,deep geophysical field,and time-space distribution of seismicities can be usedas the main seismogeological indicators to identify the newly-generated seismic rupture zone(NSRZ).According to their formation and evolution process,the NSRZs can be divided intothree types:pre-rupture-isolated,quasi-rupture-discontinuous and major-rupture-connected.In a pre-rupture-isolated NSRZ,the seismicity is dominated by medium-small earthquakes.In a quasi-rupture-discontinuous NSRZ,the frequency and intensity of strong earthquakesincrease and there may even be the largest earthquake to occur.A major-rupture-connectedNSRZ is the segment where rupture has entered the mature stage;in such a zone,theintensity and duration of seismic activity depend on the constitutive condition and regionalstress field in the zone.

Identification of the Breach of Short-Term Rental Regulations in Irish Rent Pressure Zones

The housing crisis in Ireland has rapidly grown in recent years. To make a more significant profit, many landlords are no longer renting out their houses under long-term tenancies but under short-term tenancies. Regulating rentals in Rent Pressure Zones with the highest and rising rents is becoming a tricky issue. In this paper, we develop a breach identifier to check short-term rentals located in Rent Pressure Zones with potential breaches only using publicly available data from Airbnb (an online marketplace focused on short-term home-stays) and Irish government websites. First, we use a Residual Neural Network to filter out outdoor landscape photos that negatively impact identifying whether an owner has multiple rentals in a Rent Pressure Zone. Second, a Siamese Neural Network is used to compare the similarity of indoor photos to determine if multiple rental posts correspond to the same residence. Next, we use the Haversine algorithm to locate short-term rentals within a circle centered on the coordinate of a permit. Short-term rentals with a permit will not be restricted. Finally, we improve the occupancy estimation model combined with sentiment analysis, which may provide higher accuracy.

Computer-aided system for hazard zone identification in ship power plants

The most dangerous places in ships are their power plants. Particularly, they are very unsafe for operators carrying out various necessary operation and maintenance activities. For this reason, ship machinery should be designed to ensure the maximum safety for its operators. It is a very difficult task. Therefore, it could not be solved by means of conventional design methods, which are used for design of uncomplicated technical equipment. One of the possible ways of solving this problem is to provide appropriate tools, which allow us to take the operator's safety into account during a design process, especially at its early stages. A computer-aided system supporting design of safe ship power plants could be such a tool. This paper deals with developing process of a prototype of the computer-aided system for hazard zone identification in ship power plants.

Regional-scale Identification of Three-dimensional Pattern of Vegetation Landscapes

The altitudinal pattern of vegetation is usually identified by field surveys,however,these can only provide discrete data on a local mountain.Few studies identifying and analyzing the altitudinal vegetation pattern on a regional scale are available.This study selected central Inner Mongolia as the study area,presented a method for extracting vegetation patterns in altitudinal and horizontal directions.The data included a vegetation map at a 1∶1 000 000 scale and a digital elevation model at a 1∶250 000 scale.The three-dimensional vegetation pattern indicated the distribution probability for each vegetation type and the transition zones between different vegetation landscapes.From low to high elevations,there were five vegetation types in the southern mountain flanks,including the montane steppe,broad-leaved forest,coniferous mixed forest,montane dwarf-scrub and sub-alpine shrub-meadow.Correspondingly,only four vegetation types were found in the northern flanks,except for the montane steppe.This study could provide a general model for understanding the complexity and diversity of mountain environment and landscape.

永久基本农田保护片区智能识别系统iZone的建立与应用

永久基本农田划定是当前国土资源管理一项十分重要而紧迫的任务,其对维护粮食安全和控制城镇无序增长具有重要意义。永久基本农田划定不仅要满足耕地质量较高而且还要集中连片,更需要协调城镇化矛盾。因此,如何从土地利用现状数据库中提取永久基本农田保护图斑实际上是一个复杂的空间数据挖掘过程。研究利用农用地分等成果定义保护片区质量,利用元胞自动机模拟分析土地利用矛盾,利用种子扩充算法进行保护片区搜索,利用神经网络进行耕地保护压力预警。基于C#和Arc Engine10.1将多种空间数据挖掘模型进行集成,构成了面向全域永久基本农田识别的智能系统工具包iZone,并在广东省高要区金利镇进行实例应用。研究表明,iZone能按既定规则从土地利用现状数据库中提取保护图斑,有效避免了人为划定的过多主观性,并且能获得与人工方案相当乃至更好的表现。iZone利用复杂地理计算技术进行永久基本农田智能识别,可提高永久基本农田划定工作的科学性。

Parameter estimation for dual-rate sampled Hammerstein systems with dead-zone nonlinearity

The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.

Logging-based assessment of low-resistivity oil zones:A case study from Sudan

The reservoirs in the N oilfield in Sudan feature a complex sedimentary environment,which has led to a widespread development of low-resistivity oil zones,accounting for as high as 37%of the total oil zones.In this case,a large number of oil zones will be misinterpreted using conventional methods.Based on the analysis of the core data and logging curves of the study area,this study concludes that the lowresistivity oil zones are formed mainly due to the high irreducible water saturation caused by the high content of illite and smectite and complex pore structure,the additional electrical conductivity induced by clay minerals,and the difference in formation water salinity between the oil zones and water zones.Furthermore,four methods are proposed to qualitatively identify these oil zones and water zones,namely the relationship analysis of five reservoir properties,cross-plotting of sensitive parameters,analysis of pressure testing data,and multi-well correlation.Furthermore,the study quantitatively calculates the initial oil saturation using the capillary pressure data,thus avoiding the conventional empirical saturation formulas depending on electrical resistivity and solving the difficulty in calculating oil saturation of low-resistivity oil zones.Finally,precise logging processing and interpretation of 95 wells in the study area are conducted using the above-mentioned comprehensive assessment system for low-resistivity oil zones.As a result,59 oil zones are newly discovered in 43 wells.Moreover,it is recommended that 17 oil zones in 12 wells should be tested,of which 11 oil zones have been tested as recommended,all proven to be high production oil zones after perforation.The coincidence rate of logging interpretation increases from 75%to 94.3%,and the original oil in place(OOIP)increases by 57.42 million barrels.All these indicate that the assessment system proposed is suitable for low-resistivity zones.

基于深度学习的特高压三端混合直流输电线路波形特征故障区域判别方法

针对将现有直流线路故障区域识别方法应用于特高压三端混合直流输电线路时,存在难以区分T区两侧故障、耐过渡电阻能力弱和阈值整定困难的问题,提出一种利用深度学习及波形特征进行特高压三端混合直流输电线路故障区域识别的方法。首先,对三端混合直流线路不同故障区域进行故障特征分析;然后,对线模电压和线模电流进行多尺度小波分解,提取线模电流中低频分量和线模电压高频分量,结合正负极电压波形特征,组成深度学习模型的输入量,并将故障区域作为输出量,构建深度学习故障区域识别模型;最后,用训练过的深度学习模型对获取的故障特征量进行处理,以实现故障区域识别的目的。通过大量仿真实验,验证了所提故障区域识别方法具有准确率高和基本不受过渡电阻影响的特性。

用途管制导向下历史空间边界识别方法研究

当前,作为重要资源的历史空间受制于传统边界认知模式,在管理中存在范围模糊、对象不明等问题。以用途管制为导向,基于价值关联的时间逻辑、空间逻辑分析历史空间边界的形成机制,以历史空间价值为统领,构建历史空间三维模型,分析价值在国土空间层面传导关联的内在作用,整合历史空间边界识别指标,形成识别方法。在此基础上,以安徽省固镇县中心区及其县域和垓下村进行实证分析,提出历史空间用途管制范围的分区分层、融入体系的管控研究方法,为建立健全历史空间用途管制制度提供研究基础。

中国煤成气地质理论研究进展与重点勘探领域

通过系统梳理煤成气地质理论的研究进展,分析煤成气对中国天然气储量和产量以及对主要产气盆地天然气勘探的贡献,并综合评价中国煤成气重点的有利勘探区带。取得的主要地质认识如下:①煤系是良好气源岩,生烃以气为主,以油为辅;②建立了基于稳定同位素、轻烃组分、生物标志物为基础的天然气成因鉴别指标体系;③提出了以“生气强度大于20×10^(8)m^(3)/km^(2)”指标为代表的大气田形成的定量/半定量主控因素,为大气田发现指明了方向;④煤成气是中国当前天然气储量和产量的主体,占比均超过55%,支撑塔里木盆地、四川盆地和鄂尔多斯盆地成为中国天然气主力产区;⑤煤岩气是煤成气未来勘探的重大领域,重点区带包括鄂尔多斯盆地乌审旗—米脂地区石炭系本溪组、四川盆地川中—蜀南地区二叠系龙潭组、准噶尔盆地陆梁隆起及南缘侏罗系西山窑组等;⑥煤系致密气是主要的增储上产领域,有利勘探区(带)包括:鄂尔多斯盆地南部和渤海湾盆地石炭系—二叠系致密气、四川盆地川中—川西过渡带三叠系须家河组致密气;⑦准噶尔盆地南缘侏罗系是下一步重要的常规煤成气有利勘探区带。上述研究认识对于进一步发展和完善中国煤成气理论,指导煤成气田勘探具有重要理论和实际意义。

“断层阴影”识别与校正方法——以松辽盆地升平构造为例

地层错断往往引起速度横向突变,导致在时间域地震资料中出现“断层阴影”现象,影响地质解释结果及圈闭评价等。为此,以松辽盆地升平构造为例,分析“断层阴影”现象,提出了正演模拟法、井震结合地层对比法和平均速度成图法三种识别方法;在此基础上,针对“断层阴影”,提出了高精度速度场校正和时间域层位校正两种校正方法。结果表明,高精度速度场校正法可以实现数据体的校正,适应性更广;时间域层位校正法可以实现层位的校正,具有快速、简便的优势。该方法对类似地区具有借鉴意义。

煤矿采空区覆岩“三带”智能识别方法

为了探明煤矿采空区覆岩破坏类型与裂隙发育情况,快速准确划分采空区覆岩弯曲带、断裂带、垮落带(简称“三带”),提出智能识别方法,为制定采空区治理方案提供依据。以山东某矿区采空区为例,采用贝叶斯在线变化点检测(Bayesian Online Changepoint Detection,BOCD)算法对钻进过程中的冲洗液漏失量和钻速数据在煤矿采空区“三带”界限处的变化及响应特征进行分析。以勘察规范中有关“三带”高度计算经验公式作为约束条件,对冲洗液漏失量和钻速数据中的候选变化点进行检测、优选,进而确定煤矿采空区“三带”界限深度。智能识别的结果与实际值吻合,其中,弯曲带下限、断裂带下限、垮落带下限的深度误差分别为+0.67、+0.31和+0.52m,弯曲带、断裂带和垮落带的高度误差分别为+0.14%、-0.63%和+2.49%。基于钻进数据的采空区覆岩“三带”智能识别方法精度满足设计需要,切实可行。该方法将钻进数据与经验公式相结合,在钻进过程中即可完成“三带”界限的划分,充分发挥数据的时效性,避免了技术人员主观判断对识别结果产生影响。相较于依靠多种方式综合确定“三带”界限的传统方法,该智能识别方法显著提高了“三带”划分的时效性和准确性。

无锡市近地面大气CO_(2)和CH_(4)车载移动观测及热点识别研究

城市是温室气体的排放热点。基于3台便携式CO_(2)/CH_(4)/H_(2)O分析仪于2022年夏季观测无锡市近地面大气CO_(2)和CH_(4)浓度。结果表明:(1)近地面大气CO_(2)和CH_(4)浓度高于背景站的,且不同功能区CO_(2)和CH_(4)浓度存在差异。近地面大气CO_(2)浓度与城市背景站差值(ΔCO_(2))空间分布呈现为商业居民混合区的>住宅区的>工业区的>林区的>太湖景区的;而CH_(4)浓度的差值(ΔCH_(4))空间分布呈现为商业居民混合区的>林区的>住宅区的>工业区的>太湖景区的。(2)车辆排放是无锡市主要的CO_(2)和CH_(4)排放源,污水处理厂是主要的CH_(4)排放源,排放热点附近大气CO_(2)和CH_(4)浓度较周围高约30%及以上。(3)隧道内CH_(4)∶CO_(2)值为0.0014±0.00001,表明无锡市车辆以CO_(2)排放为主。

哈萨克斯坦南图尔盖盆地Doshan斜坡带岩性油气藏储层预测方法

综合利用钻井、测井、地震等资料,分析了哈萨克斯坦南图尔盖盆地Doshan区块中部斜坡带沉积特征,并提出了一种岩性油气藏储层预测方法,识别出岩性圈闭,地震属性分析验证了储层预测结果的可靠性。研究结果表明:(1)哈萨克斯坦南图尔盖盆地Doshan斜坡带中—下侏罗统沉积时构造活动强烈,发育少量断裂,以湖相沉积为主,可分为SQ4—SQ6共3个沉积期,分别对应埃巴林组(J_(1)ab)、多尚组(J_(2)ds)和卡拉甘塞组(J_(2)kr),SQ6时期发生大规模湖侵,扇三角洲呈裙带状展布在边缘断层一侧,半深湖范围扩大;三角洲前缘为岩性圈闭发育的有利相带。(2)储层预测方法为以井-震标定结果确定地层界线,以基于声波曲线重构的岩石物理分析校正井径的影响,以基于调谐厚度的正演模型分析识别砂体,以高分辨率岩性储层地震反演技术对单砂层进行识别。(3)研究区岩性圈闭主要分布于中—下侏罗统,发育于坡折控砂条件下的一系列构造带上。地震属性分析结果与沉积特征吻合度较高。(4)研究区中—下侏罗统的坡折位置发育一系列岩性圈闭,在高分辨率地震剖面上表现为强振幅、高阻抗特征,是勘探有利区。

外肢体机器人驱动单元低速死区自适应补偿方法

为提高外肢体机器人高功率密度驱动单元的控制精度,提出一种低速死区自适应补偿方法。首先基于最小二乘系统辨识与阻尼辨识方法建立驱动单元模型,然后提出驱动单元的计算力矩控制方法,最后提出驱动单元的低速死区自适应补偿方法,并进行了实验验证。研究结果表明,与传统PID控制方法相比,采用计算力矩控制方法后驱动单元最大角度跟踪误差减小了约53%,平均角度跟踪误差减小了约38%;在计算力矩控制方法的基础上,采用低速死区自适应补偿方法后,驱动单元最大角度跟踪误差减小了约45%,平均角度跟踪误差减小了约60%,驱动单元的控制精度得到了显著提高。

基于切比雪夫窗的配电电缆缺陷诊断优化研究

电缆输入阻抗谱加窗傅里叶变换后主瓣宽度过大,导致电缆末端附近缺陷定位“死区”过大。为解决该问题,提出一种基于切比雪夫窗的配电电缆缺陷定位改进方法。首先,建立电缆分布参数模型,结合电缆输入阻抗谱阐述局部缺陷定位原理;然后,通过海明窗、布莱克曼窗和切比雪夫窗对电缆输入阻抗谱加窗进行仿真研究,对比分析各窗函数性能;最后,由电缆阻抗相位谱构造诊断函数并结合切比雪夫窗实现缺陷定位与缺陷类型识别。对长度为100 m的10 kV XLPE电缆进行仿真研究,所得结果表明:与直接对电缆阻抗谱加切比雪夫窗处理相比,所提方法不仅能将距电缆首端2 m处缺陷定位相对误差由0.467%减小至0.029%,而且定位“死区”从距电缆末端6m减小至3 m,同时能够根据缺陷处波形特征识别不同缺陷类型。

基于开放街道地图和兴趣点的上海城市功能区识别与分析

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