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101.
The chemical oxygen demand (COD) parameter of a wastewater treatment plant is predicted based on wavelet decomposition, entropy, and neural networks (NN) for rapid COD analysis. This paper also describes the usage of wavelet and NNs for parameter prediction. Data from a wastewater treatment plant in Malatya, Turkey, were used. This dataset consists of daily values of influents and effluents for a year. To reduce the dimension of input parameters and to decrease the NN training time, wavelet decomposition and entropy were used. Test results were presented graphically. The test results of the trained model were found to be closer to the measured COD values. 相似文献
102.
XIONG Fahui YANG Jingsui Paul T. ROBINSON Yildirim DILEK MILUSHI Ibrahim XU Xiangzhen ZHANG Zhongming ZHOU Wen CHEN Yanhong HUANG Zhu LAI Shengming ZHANG Lan 《《地质学报》英文版》2015,89(Z2):102-102
<正>The ultramafic massif of Bulqiza,which belongs to the eastern ophiolitic belt of Albania,is the most important area for metallurgical chromitite ores.The massif consists of a thick(4 km)rock sequence,with a generalized profile from the bottom to the top as follows.The tectonite 相似文献
103.
MILUSHI Ibrahim 《《地质学报》英文版》2015,89(Z2):61-64
<正>1 A Short Introduction on the Albanian Ophiolite Albanian ophiolite(or Mirdita ophiolite)represents a remnant of the Tethyan oceanic lithosphere in the territory of Albania,as an elongated belt from south to the north,about 250 km long and 30-50 km wide.It covers an area of about 4300 km2 or 1/7 of the territory of Albania and is 相似文献
104.
Almadani Sattam Abdelrahman Kamal Ibrahim Elkhedr Al-Bassam Abdulaziz Al-Shmrani Awad 《Arabian Journal of Geosciences》2015,8(4):2347-2357
Arabian Journal of Geosciences - Microtremor horizontal-to-vertical spectral ratio (HVSR) method has been conducted at 33 sites in Ahud Rufeidah urban expansion zone in order to assess the... 相似文献
105.
Muhammad Umer Altaf Arnold W. Heemink Martin Verlaan Ibrahim Hoteit 《Ocean Dynamics》2011,61(8):1093-1105
The Dutch continental shelf model (DCSM) is a shallow sea model of entire continental shelf which is used operationally in
the Netherlands to forecast the storm surges in the North Sea. The forecasts are necessary to support the decision of the
timely closure of the moveable storm surge barriers to protect the land. In this study, an automated model calibration method,
simultaneous perturbation stochastic approximation (SPSA) is implemented for tidal calibration of the DCSM. The method uses
objective function evaluations to obtain the gradient approximations. The gradient approximation for the central difference
method uses only two objective function evaluation independent of the number of parameters being optimized. The calibration
parameter in this study is the model bathymetry. A number of calibration experiments is performed. The effectiveness of the
algorithm is evaluated in terms of the accuracy of the final results as well as the computational costs required to produce
these results. In doing so, comparison is made with a traditional steepest descent method and also with a newly developed
proper orthogonal decomposition-based calibration method. The main findings are: (1) The SPSA method gives comparable results
to steepest descent method with little computational cost. (2) The SPSA method with little computational cost can be used
to estimate large number of parameters. 相似文献
106.
107.
A rainfall‐runoff model based on an artificial neural network (ANN) is presented for the Blue Nile catchment. The best geometry of the ANN rainfall‐runoff model in terms of number of hidden layers and nodes is identified through a sensitivity analysis. The Blue Nile catchment (about 300 000 km2) in the Nile basin is selected here as a case study. The catchment is classified into seven subcatchments, and the mean areal precipitation over those subcatchments is computed as a main input to the ANN model. The available daily data (1992–99) are divided into two sets for model calibration (1992–96) and for validation (1997–99). The results of the ANN model are compared with one of physical distributed rainfall‐runoff models that apply hydraulic and hydrologic fundamental equations in a grid base. The results over the case study area and the comparative analysis with the physically based distributed model show that the ANN technique has great potential in simulating the rainfall‐runoff process adequately. Because the available record used in the calibration of the ANN model is too short, the ANN model is biased compared with the distributed model, especially for high flows. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
108.
109.
Ahmed Abdulkareem Ahmed Biswajeet Pradhan Maher Ibrahim Sameen Ali Muayad Makky 《Arabian Journal of Geosciences》2018,11(11):280
This study proposed a workflow for an optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data. The method is validated on a set of data captured over a part of Selangor located in the Peninsular Malaysia. The method comprised four components including image segmentation, Taguchi optimization, attribute selection using random forest, and rule-based feature extraction. Results indicated the robustness of the proposed approach as the area under curve of forest; grassland, old oil palm, rubber, urban tree, and young oil palm were calculated as 0.90, 0.89, 0.87, 0.87, 0.80, and 0.77, respectively. In addition, results showed that SAR data is very useful for extracting rubber and young oil palm trees (given by random forest importance values). Finally, further research is suggested to improve segmentation results and extract more features from the scene. 相似文献
110.
Hickmat Hossen Mona G. Ibrahim Wael Elham Mahmod Abdelazim Negm Kazuo Nadaoka Oliver Saavedra 《Arabian Journal of Geosciences》2018,11(5):93
This study assesses the changes in surface area of Manzala Lake, the largest coastal lake in Egypt, with respect to changes in land use and land cover based on a multi-temporal classification process. A regression model is provided to predict the temporal changes in the different detected classes and to assess the sustainability of the lake waterbody. Remote sensing is an effective method for detecting the impact of anthropogenic activities on the surface area of a lagoon such as Manzala Lake. The techniques used in this study include unsupervised classification, Mahalanobis distance supervised classification, minimum distance supervised classification, maximum likelihood supervised classification, and normalized difference water index. Data extracted from satellite images are used to predict the future temporal change in each class, using a statistical regression model and considering calibration, validation, and prediction phases. It was found that the maximum likelihood classification technique has the highest overall accuracy of 93.33%. This technique is selected to observe the changes in the surface area of the lake for the period from 1984 to 2015. Study results show that the waterbody surface area of the lake declined by 46% and the area of floating vegetation, islands, and land agriculture increased by 153.52, 42.86, and 42.35% respectively during the study period. Linear regression model prediction indicates that the waterbody surface area of the lake will decrease by 25.24% during the period from 2015 to 2030, which reflects the negative impact of human activities on lake sustainability represented by a severe reduction of the waterbody area. 相似文献