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排序方式: 共有1378条查询结果,搜索用时 15 毫秒
1.
This paper describes the evaluation of a WSD method withinSENSEVAL. This method is based on Semantic Classification Trees (SCTs)and short context dependencies between nouns and verbs. The trainingprocedure creates a binary tree for each word to be disambiguated. SCTsare easy to implement and yield some promising results. The integrationof linguistic knowledge could lead to substantial improvement.  相似文献   
2.
对合肥市郊县的绿化造林现状作了分析,提出了切实可行的措施。  相似文献   
3.
In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.  相似文献   
4.
This paper evaluates the performance of different types of Regression Trees (RTs) in a real problem of very short-term wind speed prediction from measuring data in wind farms. RT is a solidly established methodology that, contrary to other soft-computing approaches, has been under-explored in problems of wind speed prediction in wind farms. In this paper we comparatively evaluate eight different types of RTs algorithms, and we show that they are able obtain excellent results in real problems of very short-term wind speed prediction, improving existing classical and soft-computing approaches such as multi-linear regression approaches, different types of neural networks and support vector regression algorithms in this problem. We also show that RTs have a very small computation time, that allows the retraining of the algorithms whenever new wind speed data are collected from the measuring towers.  相似文献   
5.
海堤外滩地种树效果及对行洪影响   总被引:11,自引:0,他引:11  
本文在野外调查的基础上,以新会和斗门两地堤外滩地种植适生防浪树为例,介绍了珠江三角洲河口区堤外滩地种植适生防浪树的实践与经验,及其固滩固岸,防浪护堤的作用和效果。对三角洲不同水文区的河道滩槽宽度比进行统计分析,据不同水文区受灾的主要矛盾,指出滩地种树的利和弊及其对行洪的影响。  相似文献   
6.
In a sensor network with a large number of densely populated sensor nodes, a single target of interest may be detected by multiple sensor nodes simultaneously. Data collected from the sensor nodes are usually highly correlated, and hence energy saving using in-network data fusion becomes possible. A traditional data fusion scheme starts with dividing the network into clusters, followed by electing a sensor node as cluster head in each cluster. A cluster head is responsible for collecting data from all its cluster members, performing data fusion on these data and transmitting the fused data to the base station. Assuming that a sensor node is only capable of handling a single node-to-node transmission at a time and each transmission takes T time-slots, a cluster head with n cluster members will take at least nT time-slots to collect data from all its cluster members. In this paper, a tree-based network structure and its formation algorithms are proposed. Simulation results show that the proposed network structure can greatly reduce the delay in data collection.  相似文献   
7.
In this article, discrimination models are presented, relating the origin of honey samples to several variables, being the concentrations of different cations and anions in the honey samples measured by ion chromatography, and parameters that measure/reflect the antioxidant activity of the honey samples. The unsupervised method, principal component analysis, and supervised discrimination methods, such as linear and quadratic discriminant analysis, and classification and regression trees (CART), were applied to evaluate the existence of data patterns and the relationship between geographical origin and the measured parameters. The model with the best predictive ability (%CCRTEST = 66.67%), the best overall % specificity (80%) and the best overall % sensitivity (67%) was found to be CART. It was proven that the mineral content and parameters analysed can provide enough information for the geographical characterisation and discrimination of honey.  相似文献   
8.
An efficient procedure which integrates feature selection and binary decision tree construction is presented. The nonparametric approach is based on the Kolmogorov-Smirnov criterion which yields an optimal classification decision at each node. By combining the feature selection with the design of the classifier, only the most informative features are retained for classification.  相似文献   
9.
    
《Quality Engineering》2012,24(3):157-168
ABSTRACT

The production of vaccines is a complex biological process, with long cycle times and high variation in raw materials, growth rates, and test methods. Hundreds of variables are monitored for every batch of vaccine produced; however, the relationships between product quality and process variables are difficult to quantify. We describe how mining historical process data using random forests and partial least squares techniques enabled us to identify the drivers of variability in bulk vaccine yield and to implement new controls which significantly reduced the variation.  相似文献   
10.
    
《Quality Engineering》2012,24(2):107-116
This article studies the Deming cost model using a Bayesian approach when the quality characteristic of items is assumed to have a normal distribution with unknown mean. Previously, researchers studied this model by the go/no-go data. Through a Bayesian approach, the model consists of a two-stage decision that minimizes the expected total cost: The first stage decision is to determine the optimal sample size, and the second stage decision is to decide whether to stop inspection or continue to inspect the remaining items of the lot. Numerical integration is used to find an approximate solution to the model. An illustrative example is given and a numerical analysis of this example is performed to realize the effects of the model parameters. The cost difference between using the measurement data and the corresponding go/no-go data under the same probability assumptions and cost structure is also investigated.  相似文献   
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