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41.
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Charitable foundations and government programmes should endeavour to allocate their limited resources to best serve their constituents. Yet, mathematical programming techniques are rarely used despite overwhelming evidence of their superiority in selecting projects that yield higher levels of total benefits. We present a novel ‘hybrid selection model’ that combines binary linear programming and heuristic rank-based models applied to two case studies. The first case focuses on providing services to women and shows a hybrid model would have selected the top three ‘signature’ projects and maintained an above-average overall project benefit while securing a 180% improvement in the number of projects funded, a 66% improvement in the number of women served and a 132% improvement in the total benefit achieved. In the second case, we apply the hybrid approach to data from the US government’s largest forest preservation programme and demonstrate that the hybrid approach could allow the programme to select up to 11 top-scoring projects while still achieving a 97% gain in the total overall benefit compared to their traditional method. These case studies show that the hybrid approach has the potential to be applied in a variety of settings and improve how foundations and programmes achieve their goals. 相似文献
43.
Gurhan Uysal 《现代会计与审计》2014,(1):55-58
This paper aims to find unit cost of a product for firms. It establishes a linear cost model to find unit cost. Linear goal programs assume a direct relationship between independent variable and dependent variable. Dependent variable of linear model is unit cost. Independent variables are cost accounting variables. They are supply cost, labor cost, and administration cost. This study assumes a direct relationship between supply-labor-administration costs and unit cost. Therefore, it establishes a linear cost model. The major research question of this study is to apply linear goal programming to cost accounting. The goal of this linear program is to find unit cost of product. This study uses quantitative method and human capital method. The main research result is linear costing model itself. 相似文献
44.
《Socio》2019
Biofuels are emerging as a prominent renewable and sustainable energy sources in developed countries. In this sense, this paper presents a case study in which a biorefinery has to be sited in Northern Spain. Thus, the strategic decision of locating such a facility is deeply investigated through strategic policy evaluation. Then, tactical decisions ranging from purchasing and transportation policies to storage protocols are carried out. Only local and limited biomass can be harvested for supplying the biorefinery through a heterogeneous vehicle fleet. Moreover two different and mutually exclusive storage strategies are evaluated: direct supply from crops to biorefinery and using intermediate-collectors. Additionally, crop exploitation factors and biorefinery sizes are used to generate several scenarios in which the strategic decision of location as well as all the tactic decisions are made. Some mixed integer linear programming models are proposed to figure out all relevant decision problems.The results suggest that the Northwest study area as the best option to locate the biorefinery and recommend the intermediate-collector storage strategy. Moreover, the key information about critical biomass, crops and times are also provided. 相似文献
45.
46.
Abstract
Background
Fraud- or theft-related crimes account for the highest number of crimes in the mental health industry in the US. 相似文献47.
《Socio》2019
Ratio type financial indicators are the most popular explanatory variables in bankruptcy prediction models. These measures often exhibit heavily skewed distribution because of the presence of outliers. In the absence of clear definition of outliers, ad hoc approaches can be found in the literature for identifying and handling extreme values. However, it is not clear how these different approaches can affect the predictive power of models. There seems to be consensus in the literature on the necessity of handling outliers, at the same time, it is not clear how to define extreme values to be handled in order to maximize the predictive power of models. There are two possible ways to reduce the bias originating from outliers: omission and winsorization. Since the first approach has been examined previously in the literature, we turn our attention to the latter. We applied the most popular classification methodologies in this field: discriminant analysis, logistic regression, decision trees (CHAID and CART) and neural networks (multilayer perceptron). We assessed the predictive power of models in the framework of tenfold stratified crossvalidation and area under the ROC curve. We analyzed the effect of winsorization at 1, 3 and 5% and at 2 and 3 standard deviations, furthermore we discretized the range of each variable by the CHAID method and used the ordinal measures so obtained instead of the original financial ratios. We found that this latter data preprocessing approach is the most effective in the case of our dataset. In order to check the robustness of our results, we carried out the same empirical research on the publicly available Polish bankruptcy dataset from the UCI Machine Learning Repository. We obtained very similar results on both datasets, which indicates that the CHAID-based categorization of financial ratios is an effective way of handling outliers with respect to the predictive performance of bankruptcy prediction models. 相似文献
48.
我国是受水害最严重的国家,奥灰水突水是我国很多煤矿在安全生产中急待解决的问题。山西王家岭煤业集团公司王家岭煤矿就面临着开采9号煤层底板奥灰水突水威胁的安全问题。结合王家岭煤矿实际钻孔数据,运用突水系数法、多层叠加抗压强度比值系数法分别对9号煤层进行突水危险性预测,并进行相互对比,根据计算所得结果得出9号煤层底板易发生突水区。 相似文献
49.
Byeong U. Park Enno Mammen Young K. Lee Eun Ryung Lee 《Revue internationale de statistique》2015,83(1):36-64
Varying coefficient regression models are known to be very useful tools for analysing the relation between a response and a group of covariates. Their structure and interpretability are similar to those for the traditional linear regression model, but they are more flexible because of the infinite dimensionality of the corresponding parameter spaces. The aims of this paper are to give an overview on the existing methodological and theoretical developments for varying coefficient models and to discuss their extensions with some new developments. The new developments enable us to use different amount of smoothing for estimating different component functions in the models. They are for a flexible form of varying coefficient models that requires smoothing across different covariates' spaces and are based on the smooth backfitting technique that is admitted as a powerful technique for fitting structural regression models and is also known to free us from the curse of dimensionality. 相似文献
50.
José García-Pérez María del Mar López-Martín Catalina García-García Román Salmerón-Gómez 《Revue internationale de statistique》2020,88(3):776-792
Justifying ridge regression from a geometrical perspective is one of the main contributions of this paper. To the best of our knowledge, this question has not been treated previously. This paper shows that ridge regression is a particular case of raising procedures that provide greater flexibility by transforming the matrix X associated with the model. Thus, raising procedures, based on a geometrical idea of the vectorial space associated with the columns of matrix X , lead naturally to ridge regression and justify the presence of the well-known constant k on the main diagonal of matrix X ′ X . This paper also analyses and compares different alternatives to raising with respect to collinearity mitigation. The results are illustrated with an empirical application. 相似文献