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81.
The shortage of potassium salt seriously restricts the development of China's agriculture. Increasing the exploration and development of potash will help improve the self-sufficiency of potassium in China. With rich potassium salt resources, Sichuan basin is one of the most important research areas for potash exploration and development in China. Polyhalite is an important solid potassium salt mineral in Sichuan basin, often intercalated in rock minerals such as anhydrite, rock salt and dolomite. Aiming at the problem that conventional log interpretation methods are difficult to accurately identify polyhalites, this paper proposed a new Support Vector Machine (SVM) recognition method based on Particle Swarm Optimization (PSO) to classify polyhalites in Sichuan basin. Based on particle swarm optimization and support vector machine theory, combined with logging interpretation theory, the effective data sensitive to polyhalite logging response were selected as input samples to generate training sets and test sets randomly. The Radial Basis Function (RBF) parameters were optimized by particle swarm optimization, and the classification and prediction model of polyhalite was established. Compared with mud logging results, the recognition accuracy of SVM model based on particle swarm optimization reached 97.5758%, which is obviously better than that of SVM model optimized by cross validation method in recognition accuracy and speed. The results show that the model has broad application prospects in potash exploration in Sichuan basin. 相似文献
82.
基于拓扑网络研究海州湾食物网结构与复杂性 总被引:1,自引:0,他引:1
针对食物网结构与复杂性的研究有助于深入解析食物网的功能、营养动力和能量转化过程。本文根据2011年3?12月在海州湾及其邻近海域进行的5个航次的渔业资源底拖网调查资料以及胃含物分析数据,基于11个拓扑网络指数,构建了海州湾拓扑网络,研究海州湾食物网的结构与复杂性。结果表明,本文分析的海州湾食物网物种数S为93,连接数L为1 021,每个物种的相互作用数量L/S为10.98,连接性L/S2为0.12;顶级物种、中间物种、基础物种的比例分别为29%、69%和2%;食物网的杂食性指数为87%,连接复杂性指数SC为22.20,特征路径长度ChPath为2.11,聚类系数CC为0.23。通过每个物种的相互作用数量和连接性的研究显示,L/S和L/S2的值都处在正常范围内,所以海州湾食物网的复杂性仍保持较高水平。通过物种比例、杂食性指数、连接复杂性指数、特征路径长度、聚类系数对食物网结构分析,发现海州湾食物网结构处于稳定状态,能够在一定程度上抵御外界环境的扰动,保证生态系统功能的正常运行。通过对海州湾食物网结构与复杂性的研究,将为今后海州湾食物网功能的深入研究以及海州湾渔业资源的科学管理提供重要依据。 相似文献
83.
Melih Basaraner Sinan Cetinkaya 《International journal of geographical information science》2017,31(10):1952-1977
Shape characterisation is important in many fields dealing with spatial data. For this purpose, numerous shape analysis and recognition methods with different degrees of complexity have so far been developed. Among them, relatively simple indices are widely used in spatial applications, but their performance has not been investigated sufficiently, particularly for building footprints (BFs). Therefore, this article focuses on BF shape characterisation with shape indices and classification schemes in a GIS environment. This study consists of four phases. In the first phase, the criteria for BF shape complexity were identified, and accordingly, benchmark data was constructed by human experts in three shape complexity categories. In the second phase, 18 shape indices were selected from the literature and automatically computed in GIS. The performance of these indices was then statistically assessed with histograms, correlation matrix and boxplots, and consequently four indices were found to be appropriate for further investigation. In the third phase, two new indices (Equivalent Rectangular index and Roughness index) were proposed with the objective to measure some BF shape characteristics more efficiently. The proposed indices also were found to be appropriate with the same statistical assessment procedures. In the final phase, BF shape complexity categories were created with the pairs of six appropriate indices and four choropleth mapping classification schemes (equal intervals, natural break, standard deviation, and custom) in GIS. The performance of the index–scheme pairs was assessed against the benchmark data. The findings demonstrated that both new indices and two of the selected indices (Convexity and Rectangularity) delivered higher performance. The custom classification scheme was found more ideal to reveal absolute shape complexity with the index value ranges derived from the boxplots while the other classification schemes were more appropriate to reveal relative shape complexity. 相似文献
84.
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86.
Developing,choosing and using landscape evolution models to inform field‐based landscape reconstruction studies 下载免费PDF全文
A.J.A.M. Temme J. Armitage M. Attal Wouter van Gorp T.J. Coulthard J.M. Schoorl 《地球表面变化过程与地形》2017,42(13):2167-2183
Landscape evolution models (LEMs) are an increasingly popular resource for geomorphologists as they can operate as virtual laboratories where the implications of hypotheses about processes over human to geological timescales can be visualized at spatial scales from catchments to mountain ranges. Hypothetical studies for idealized landscapes have dominated, although model testing in real landscapes has also been undertaken. So far however, numerical landscape evolution models have rarely been used to aid field‐based reconstructions of the geomorphic evolution of actual landscapes. To help make this use more common, we review numerical landscape evolution models from the point of view of model use in field reconstruction studies. We first give a broad overview of the main assumptions and choices made in many LEMs to help prospective users select models appropriate to their field situation. We then summarize for various timescales which data are typically available and which models are appropriate. Finally, we provide guidance on how to set up a model study as a function of available data and the type of research question. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
87.
In this paper, statistics are taken on the co-seismic response of underground fluid in Yunnan to the Nepal MS8.1 earthquake, and the co-seismic response characteristics of the water level and water temperature are analyzed and summarized with the digital data. The results show that the Nepal MS8.1 earthquake had greater impact on the Yunnan region, and the macro and micro dynamics of fluids showed significant co-seismic response. The earthquake recording capacity of water level and temperature measurement is significantly higher than that of water radon and water quality to this large earthquake; the maximum amplitude and duration of co-seismic response of water level and water temperature vary greatly in different wells. The changing forms are dominated by fluctuation and step rise in water level, and a rising or falling restoration in water temperature. From the records of the main shock and the maximum strong aftershock,we can see that the greater magnitude of earthquake, the higher ratio of the occurrence of co-seismic response, and in the same well, the larger the response amplitude, as well as the longer the duration. The amplitude and duration of co-seismic response recorded by different instruments in a same well are different.Water temperature co-seismic response almost occurred in wells with water level response, indicating that the well water level and water temperature are closely related in co-seismic response, and the well water temperature seismic response was caused mainly by well water level seismic response. 相似文献
88.
Predicting groundwater level of wells in the Diyala River Basin in eastern Iraq using artificial neural network 下载免费PDF全文
Al-Mansourieh zone is a part of Al-Khalis City within the province of Diyala and located in the Diyala River Basin in eastern Iraq with a total area about 830 km2.Groundwater is the main water source for agriculture in this zone.Random well drilling without geological and hydraulic information has led the most of these wells to dry up quickly.Therefore,it is necessary to estimate the levels of groundwater in wells through observed data.In this study,Alyuda NeroIntelligance 2.1 software was applied to predict the groundwater levels in 244 wells using sets of measured data.These data included the coordinates of wells(x,y),elevations,well depth,discharge and groundwater levels.Three ANN structures(5-3-3-1,5-10-10-1 and 5-11-11-1)were used to predict the groundwater levels and to acquire the best matching between the measured and ANN predicted values.The coefficient of correlation,coefficient determination(R2)and sum-square error(SSE)were used to evaluate the performance of the ANN models.According to the ANN results,the model with the three structures has a good predictability and proves more effective for determining groundwater level in wells.The best predictor was achieved in the structure 5-3-3-1,with R2 about 0.92,0.89,0.84 and 0.91 in training,validation,testing and all processes respectively.The minimum average error in the best predictor is achieved in validation and testing processes at about 0.130 and 0.171 respectively.On the other hand,the results indicated that the model has the potential to determine the appropriate places for drilling the wells to obtain the highest level of groundwater. 相似文献
89.
90.
孙吴-嘉荫盆地嘉D1井孢粉地层学研究 总被引:3,自引:0,他引:3
对孙吴一嘉荫盆地北部逊克县的嘉DI井采集的孢粉和沟鞭藻类化石进行了分析研究,划分出?个特征较明显的孢粉组合:富饶组Betulaepollenires-Schizaeoisporites-Polypodiaceaesporites组合,总体反映晚白垩世晚期Maastrichtian期的特点;太平林场组Gothanipollis-Gabionisporis-Balmeisporites组合,时代为晚白垩世Santonian—Campanian期;淘淇河组上段Hammenia-Taxodiaceaepollenites-Appendicisportes组合,时代为早白垩Aptian—Albian期;淘淇河组下段Cicatricosporites-Cyathidites-Osmundacidites组合,时代为早白垩Valanginan—Barrcmian期。这是迄今该地区据钻井实际资料所发现的较连续孢粉组合序列。 相似文献