Water use, growth and yield of green gram under rainfed upland crop sequences in Gangetic Plains of Indian sub-tropics

A field experiment was conducted to study the effect of different crop sequences on water use, growth and yield of green gram (Vigna radiata (L) Wilezek) during 1992-93 and 1993-94 under rainfed upland condition in Indo-Gangetic plains of West Bengal. Green gram sown in the month of March as pre-rainy (summer) season crop, as and when the winter crops vacated the land, produced highest dry matter of 372 gm-2 which was significantly highest in black gram-yellow sarson sequence.The results of the field experimentation revealed that green gram gave highest grain yield to the extent of 10.80 q/ha when sown after black gram (rainy season) followed by yellow sarson (winter season) while the crop produced 10.63 q/ha under sesame-yellow sarson sequence. Highest water use of 267mm was achieved in green gram under black gram-yellow sarson sequence and the crop gave water use efficiency of 4.07 kg ha-1mm-1 under black gram-yellow sarson sequences.     

Water use, growth and yield of green gram under rainfed upland crop sequences in Gangetic Plains of Indian sub-tropics

A field experiment was conducted to study the effect of different crop sequences on water use, growth and yield of green gram (Vigna radiata (L) Wilezek) during 1992-93 and 1993-94 under rainfed upland condition in Indo-Gangetic plains of West Bengal. Green gram sown in the month of March as pre-rainy (summer) season crop, as and when the winter crops vacated the land, produced highest dry matter of 372 gm-2 which was significantly highest in black gram-yellow sarson sequence. The results of the field experimentation revealed that green gram gave highest grain yield to the extent of 10.80 q/ha when sown after black gram (rainy season) followed by yellow sarson (winter season) while the crop produced 10.63 q/ha under sesame-yellow sarson sequence. Highest water use of 267 mm was achieved in green gram under black gram-yellow sarson sequence and the crop gave water use efficiency of 4.07 kg ha-1mm-1 under black gram-yellow sarson sequences.     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.     

Aspects of the loss-on-ignition (LOI) technique in the context of clay-rich, glaciolacustrine sediments

The loss‐on‐ignition (LOI) technique for organic matter determination is evaluated with reference to clay‐rich, glaciolacustrine sediments. Examples of the use of LOI in glaciolacustrine literature are inconsistent in their methodology, and standardisation is called for. Problems with application of the technique to glaciolacustrine sediments stem mainly from the effects of additional weight loss due to release of structurally bound water and exposure time to ignition temperatures. Exposure time should be increased from 1 hour to 2.5 hours in the light of significant additional weight loss occurring between 2 and 2.5 hours in clay‐rich samples. The reason for this sudden increase in LOI after 2 hours (up to 86% of total LOI in some cases) appears to be the build‐up of a distinct surface crust during heating that insulates the core of the sample from ignition temperatures. Some time between 2 and 2.5 hours, the crust breaks down and exposes the sample core to ignition temperatures, increasing weight loss significantly. Overestimation of LOI due to loss of structural water is thought to be insignificant. Replicates of LOI at 550 and 1000°C in non‐calcareous, clay‐rich (>40%) sediments, show differences of <0.25%, which, for the purpose of inferring broad changes in glacier extent in lake catchments, is an acceptable error.     

智能交通系统中的公交车辆指挥调度体系结构

该文阐述公交智能指挥调度系统总体框架，结合智能交通系统ITS(Intelligent Transport Systems)对公交智能化调度的逻辑结构和物理结构要求，分析公交车辆智能化调度系统结构体系及其模型化，探讨智能调度策略和调度机理。根据该系统总体设计框架构思，了解系统各功能间的相互关系，优化公交车辆运营管理模式，以改善现有公交系统的管理水平以及运营效率，为公交指挥调度系统的完善、提高提供可靠技术基础。     

水土流失评价数据库建立中的数据标准化研究--以中国潜在水土流失评价数据库为例

在水土流失评价数据库的建立研究中，涉及到数据的标准化问题。该研究以中国潜在水土流失评价数据库建立过程中的数据标准化研究为例，探讨建立适合水土流失评价数据标准化的方法。研究包括了水土流失数据标准化建设中的评价数据库的设计、数据的标准化。其中，数据的标准化包括数据的收集与分析、数据的录入、投影变换、其它格式向ARC/INFO格式的转换、补充编制专题文档等。     

湘北红壤坡地雨水过程的水土流失及其影响

模拟主要利用方式构建的垫面为主导因子,采用径流场实测方法,通过4a(1998～2001年)实地观测试验,剖析不同下垫面对雨水地表径流及其过程的影响。研究表明:降雨(时间分布及其强度)是影响地表径流特征的主导因素;年降雨量与地表径流量和系统水土流失量呈正相关。不同垫面地表径流产量有显著性差异;雨水径流过程的土壤和养分流失有相似的表现。在假定雨水年份的基础上,应用不同雨水年份出现概率指标,推算出:湘北红壤坡地现今利用状况下,雨水产地表径流过程的年均水土流失量及其养分(有机质、N、P、K)损失量;和可最大开发利用时,可能带来的水土流失与养分损失。提出"利用坡地集雨利用优势,构建与单元生态系统水循环平衡相适应的坡地农林复合生态系统,通过水平衡生态建设来维系生态系统的水分平衡"观点。