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621.
Modeling and spatial prediction of pre-settlement patterns of forest distribution using witness tree data 总被引:1,自引:0,他引:1
At the time of European settlement, land surveys were conducted progressively westward throughout the United States. Outside
of the original 13 colonies, surveys generally followed the Public Land Survey system in which trees, called witness trees,
were regularly recorded at 1 mi by 1 mi grid intersections. This unintentional sampling provides insight into the composition
and structure of pre-European settlement forests, which is used as baseline data to assess forest change following settlement.
In this paper, a model for the Public Land Surveys of east central Alabama is developed. Assuming that the locations of trees
of each species are realized from independent Poisson processes whose respective log intensities are linear functions of environmental
covariates (i.e., elevation, landform, and physiographic province), the species observed at the survey grid intersections
are independently sampled from a generalized logistic regression model. If all 68 species found in the survey were included,
the model would be highly over-parameterized, so only the distribution of the most common taxon, pines, will be considered
at this time. To assess the impact of environmental factors not included in the model, a hidden Gaussian random field shall
be added as a random effect. A Markov Chain Monte Carlo algorithm is developed for Bayesian inference on model parameters,
and for Bayes posterior prediction of the spatial distribution of pines in east central Alabama.
Received: June 2004 / Revised: November 2004 相似文献
622.
Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters 总被引:3,自引:0,他引:3
Two artificial neural networks (ANNs), unsupervised and supervised learning algorithms, were applied to suggest practical approaches for the analysis of ecological data. Four major aquatic insect orders (Ephemeroptera, Plecoptera, Trichoptera, and Coleoptera, i.e. EPTC), and four environmental variables (elevation, stream order, distance from the source, and water temperature) were used to implement the models. The data were collected and measured at 155 sampling sites on streams of the Adour–Garonne drainage basin (South-western France). The modelling procedure was carried out following two steps. First, a self-organizing map (SOM), an unsupervised ANN, was applied to classify sampling sites using EPTC richness. Second, a backpropagation algorithm (BP), a supervised ANN, was applied to predict EPTC richness using a set of four environmental variables. The trained SOM classified sampling sites according to a gradient of EPTC richness, and the groups obtained corresponded to geographic regions of the drainage basin and characteristics of their environmental variables. The SOM showed its convenience to analyze relationships among sampling sites, biological attributes, and environmental variables. After accounting for the relationships in data sets, the BP used to predict the EPTC richness with a set of four environmental variables showed a high accuracy (r=0.91 and r=0.61 for training and test data sets respectively). The prediction of EPTC richness is thus a valuable tool to assess disturbances in given areas: by knowing what the EPTC richness should be, we can determine the degree to which disturbances have altered it. The results suggested that methodologies successively using two different neural networks are helpful to understand ecological data through ordination first, and then to predict target variables. 相似文献
623.
We develop the non-parametric maximum likelihood estimator (MLE) of the full Mbh capture-recapture model which utilizes both initial capture and recapture data and permits both heterogeneity (h) between animals and behavioural (b) response to capture. Our MLE procedure utilizes non-parametric maximum likelihood estimation of mixture distributions (Lindsay, 1983; Lindsay and Roeder, 1992) and the EM algorithm (Dempsteret al., 1977). Our MLE estimate provides the first non-parametric estimate of the bivariate capture-recapture distribution.Since non-parametric maximum likelihood estimation exists for submodels Mh (allowing heterogeneity only), Mb (allowing behavioural response only) and M0 (allowing no changes), we develop maximum likelihood-based model selection, specifically the Akaike information criterion (AIC) (Akaike, 1973). The AIC procedure does well in detecting behavioural response but has difficulty in detecting heterogeneity. 相似文献
624.
625.
The control of 3-D temperature distribution in a utility boiler fumace is essential for the safe, economic and clean operation of pc-fired fumace with multi-burner system. The development of the visualization of 3-D temperature distributions in pcfired fumaces makes it possible for a new combustion control strategy directly with the fumace temperature as its goal to improve the control quality for the combustion processes. Studied in this paper is such a new strategy that the whole fumace is divided into several parts in the vertical direction, and the average temperature and its bias from the center in every cross section can be extracted from the visualization results of the3-D temperature distributions. In the simulation stage, a computational fluid dynamics(CFD) code served to calculate the 3-D temperature distributions in a furnace, then a linear model was set up to relate the features of the temperature distributions with the input of the combustion processes, such as the flow rates of fuel and air fed into the furnaces through all the bumers. The adaptive genetic algorithm was adopted to find the optimal combination of the whole input parameters which ensure to form an optimal 3-D temperature field in the fumace desired for the operation of boiler. Simulation results showed that the strategy could soon find the factors making the temperature distribution apart from the optimal state and give correct adjusting suggestions. 相似文献
626.
考虑了影响大气扩散的主要气象因素及其它因素,提出了一个大气SO_2污染预测模型,并运用加权实时最小二乘算法对模型进行实时辨识。这一模型尤其适用于城市及城市中SO_2日均浓度的分区预测,给出了该模型在上海地区应用的结果。 相似文献
627.
为合理确定常熟氟化工项目排污口布置方案,针对长江常熟段水环境特征,尤其是复杂的水地下形和水流流场,建立为较为准确和实用的平面二维水流水质耦合数学模型,应用剖开算子法模拟计算了3套排污方案对重点保护水域影响程序度和范围,并从水流场,水质影响评价,技术经济多角度对方案进行了比较论证,最终推荐污水江中排放的方案,为项目的工程设计和环境管理提供了科学依据。 相似文献
628.
Predicting the Range of Chinese Mitten Crabs in Europe 总被引:1,自引:0,他引:1
LEIF-MATTHIAS HERBORG† DEBORAH A. RUDNICK‡ YANG SILIANG§ DAVID M. LODGE† HUGH J. MacISAAC 《Conservation biology》2007,21(5):1316-1323
Abstract: Ecological niche modeling provides a means for predicting the potential future distribution of a nonindigenous species based on environmental characteristics of the species' native range. We applied this method to the Chinese mitten crab (Eriocheir sinensis) , a catadromous crustacean with a long history of invasion in Europe. We used genetic algorithm for rule-set prediction to predict the potential European distribution of mitten crab based on its distribution in 42 locations in its native Asia. The climatic variables, air temperature, number of days, amount of precipitation, and wetness index, contributed significantly to predictions of native distribution limits. Although the genetic algorithm for rule-set prediction model was developed for the native range, the species' extensive distribution in Europe ( n = 434) allowed independent validation of the predictions. Application of the model to Europe was successful, with 84% of occurrences in regions predicted to be suitable by >80% of the models and <4% of occurrences in areas predicted suitable by <50% of the models (mainly along the northern range). At the watershed scale, areas with established mitten crab populations had significantly higher habitat matching than sites that were not invaded. The independent validation of the Asian-based model by the European distribution revealed that predictions were highly accurate. The model also identified large areas of Europe, particularly along the Mediterranean coast, as vulnerable to future invasion. These predictions can be used to develop strategies to control the spread of mitten crab by preventing introductions into vulnerable areas. 相似文献
629.
Area-Based Refinement for Selection of Reserve Sites with the Benefit-Function Approach 总被引:1,自引:0,他引:1
Abstract: Optimization of resource use is necessary for efficient conservation planning. Many reserve-selection algorithms aim to identify representative but inexpensive networks, which may lead to selecting small sites due to their lower costs and collectively higher species richness. Nevertheless, larger sites would be preferable regarding species' long-term persistence. An area-based refinement can be used to overcome this problem. We used a reserve-planning framework in which continuous benefit functions valued representation (numbers of populations), and differential species weights were based on a species' local rarity and threatened status. We introduced a refinement based on the species-area relationship that provides relatively higher values for larger sites. We applied the proposed method to rich fen vegetation in southern Finland. The species-area refinement resulted in a network of significantly larger sites with minor trade-offs with representation (numbers of populations). Giving endangered species higher weights ensured that the trade-off occurred mostly between site size and representation of low-priority species. We recommend using a species-area refinement for practical, maximum-coverage conservation planning. 相似文献
630.