China is the largest food consumption country in the world. With the social and economic development, China's food security has become a global attention. Grain security research involves many uncertain factors: a...
详细信息
China is the largest food consumption country in the world. With the social and economic development, China's food security has become a global attention. Grain security research involves many uncertain factors: as well as quantitative and qualitative information. In order to get the grain security status comprehensively, we proposed a method to evaluate risk in grain security based on multifactor information fusion. In the method, the quantitative and qualitative information were used to construct the basic probability assignment, and the attribute weights was got based on the Analytic Hierarchy Process method. After that, the multifactor fusion results were got based on the Dempster combination rule. The effectiveness of the method was verified with a numeric example that the data comes from the yearbook of China in 2007. The Results show that the method is effective and can correctly reflect the grain safety warning degrees.
Based on analysis of basic cubic spline interpolation, the clamped cubic spline interpolation is generalized in this paper. The methods are presented on the condition that the first derivative and second derivative of...
详细信息
As an important component of data mining, Cluster Analysis (CA) has being attached importance to artificial intelligence, machine learning and other fields. Traditional clustering methods have been studied for a relat...
详细信息
As an important component of data mining, Cluster Analysis (CA) has being attached importance to artificial intelligence, machine learning and other fields. Traditional clustering methods have been studied for a relatively long time;their technologies are mature and consequently they are well-applied. However, they are insufficient in clustering accuracy, noise sensitivity, along with effect on mass of data and non-convex clustering. Granular computing, which is regarded as a label of theories, methodologies, techniques, and tools, is an emerging conceptual and computing par informationprocessing. It plays an important role informationprocessing for fuzzy, uncertainty, partial truth and soft computing and is one of the main study stream in A.I. This paper introduces some new clustering methods, such as Fuzzy clustering, Clustering Algorithm Based on Rough Set, and clustering algorithm based on quotient space theory, emphatically expounds the basic thought and typical algorithms of these methods, and comparative analysis is carried out among these methods. Finally, new clustering algorithms are prospected and we put forward the value of research direction.
Discriminant analysis, especially Fisherface and its numerous variants, have achieved great success in face recognition. However, these methods fail to work for face recognition from Single Sample per Person (SSPP), s...
详细信息
Based on analysis of cubic spline interpolation, the differentiation formulas of the cubic spline interpolation on the three boundary conditions are put up forward in this paper. At last, this calculation method is il...
详细信息
The rough neural networks (RNNs) are the neural networks based on rough set and one kind of hot research in the artificial intelligence in recent years, which synthesize the advantage of rough set to process uncertain...
详细信息
The bottleneck problem has emerged in feature selection when processing high-dimension and large-scale data, so in the past decade, the researches on feature selection have not adhere to the traditional algorithms and...
详细信息
The bottleneck problem has emerged in feature selection when processing high-dimension and large-scale data, so in the past decade, the researches on feature selection have not adhere to the traditional algorithms and ideas, showing a new trend of combining many new mathematical tools, which opens new space for feature selection applied in pattern recognition and makes further development in knowledge discovery and data mining. Granular computing has begun to take shape and show effect as a new idea of intelligentinformationprocessing, which creates the conditions for feature selection applied in data. The paper describes a new feature selection algorithm, basing on granular computing and making rough set approximation as background, the algorithm generates the granules, using a tolerance function, distinguishes noise data and inconsistent data, to achieve feature selection in the information table, and be effective for large-scale data sets.
The grey system forecasting model, neural network forecasting model and support vector machine forecasting model are proposed in this paper. Taking the road goods traffic volume from year of 1996 to 2003 in the whole ...
详细信息
As one of the important artistic styles of portrait, sketch portrait has wide applications for both digital entertainment and law enforcement. In this paper, an automatic face sketch generation approach is presented b...
详细信息
As one of the important artistic styles of portrait, sketch portrait has wide applications for both digital entertainment and law enforcement. In this paper, an automatic face sketch generation approach is presented by learning from photo-sketch pair examples. Specifically, the relationship between a face photo and its corresponding face sketch is learned on image patch level. By applying this relationship to the input face photo patch, we can infer the output face sketch patch by exploiting some regression techniques such as kNN, the Lasso and so on. Via our local regression model, we can synthesize an appealing sketch portrait from a given face photo in a few minutes. Experiments conducted on CUHK database have shown that our results are more compelling than previous methods especially in two respects: (1) our synthesized sketches preserve more identity information of the original face photo, (2) our synthesized sketches presents more pencil sketch texture.
In this paper, we denote a color image by a quaternion function, then find edge points by solving the maximum of quaternion fractional directional differentiation(QFDD)'s norm. This method is called edge detection...
详细信息
In this paper, we denote a color image by a quaternion function, then find edge points by solving the maximum of quaternion fractional directional differentiation(QFDD)'s norm. This method is called edge detection based on QFDD. Experiments indicate that the method has special advantages. Comparing with Canny, LOG, Sobel, and general fractional differentiation, we discover that QFDD has fewer false negatives in the textured regions and is also better at detecting edges which are partially defined by texture, which means we will obtain better results in the interesting regions by QFDD and these results are more consistent with the characteristics of human visual system.
暂无评论