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To try to decrease the preference of the attribute values for information gain and information gain ratio, in the paper, the authors puts forward a improved algorithm of C4.5 decision tree on the selection classification attribute. The basic thought of the algorithm is as follows: Firstly, computing the information gain of selection classification attribute, and then get an attribute of the information...
It is important to develop defense mechanisms to bolster the cyber-physical security of critical infocomm infrastructure (CII) systems. A basic method of defense for CII systems is a firewall. Since SCADA / ICS systems may be negatively impacted by latencies and delays introduced by firewalls, which will translate to real world impacts, any implemented firewall in the network should attempt to minimize...
According to the noise and overlapping characteristics of agricultural irrigation water quality monitoring data for the comprehensive evaluation may bring about the boundary fuzzy problem. This paper proposes an improved Genetic Algorithm (GA) to avoid premature convergence, the global optimal solution of the function of the Projection Pursuit (PP) function is used as the comprehensive evaluation...
Clustering is an important tool for analyzing gene expression data. Many clustering algorithms have been proposed for the analysis of gene expression data. In this article we have clustered real life gene expression data via K-Means which is one of clustering algorithms. Also, we have proposed a new method determining the initial cluster centers for K-means. We have compared results of our method...
Link prediction plays an important role in complex network analysis. It is to predict the existence of an unknown link or a future link in a network. Classical methods for link prediction evaluate the similarity of vertices based on common neighbors, and denote that every common neighbor makes equal contribution to the connection likelihood. However, common neighbors may play different roles depending...
Speech feature learning is very important for the design of classification algorithm of Parkinson's disease (PD). Existing speech feature learning method for classification of PD just pays attention to the speech feature. This paper proposed a novel hybrid feature learning algorithm which puts the features of all the speech segments of each subject together, thereby obtaining new and high efficient...
The aim of this study is to compare some classifiers' performance related to the tuples amount. The different metrics of performance has been considered, such as: Accuracy, Mean Absolute Error (MAE), and Kappa Statistic. In this research, the different numbers of tuples are considered as well. The readmission process dataset of Diabetic patients, which has been experimented, consists of 47 features...
Various indices are used for assessing vegetation and soil properties in satellite remote sensing applications. Some indices, such as NDVI and NDWI, are defined based on the sensitivity and significance of specific bands. Nowadays, remote sensing capability with a good number of bands and high spatial resolution is available. Instead of classification based on indices, this paper explores direct classification...
In the paper, a rough spatial kernelized fuzzy c-means clustering (RSKFCM) based medical image segmentation algorithm is proposed. This technique is a combination of rough set and spatial kernelized fuzzy c-means clustering (SKFCM). SKFCM is failed to remove the indistinct knowledge that is associated with each data set during the process of its assignment to a particular cluster. The rough set is...
For better resolving the safety risk early warning of the apron effectively, the attribute reduction algorithm based on Rough Set is used to simplify the set as the warning index set of the apron is too large. The improved Particle Swarm Optimization (PSO) algorithm is used to optimize the parameters of Support Vector Machine. Combined with the Rough Set and SVM which is optimized by the improved...
A cluster validity index is to evaluate the correct number of clusters when partitioning a dataset. In this paper, we propose a new cluster validity index based on two measures called dispersion and overlap for Gaussian-distributed clusters. The dispersion measure is used to estimate the situation of data spreading in a cluster. A small dispersion measure for a cluster means that data points are distributed...
Entity alignment is to link “equivalent” entities that denote the same object in the real world, which can be used to help promoting information integration and retrieval. Driven by the knowledge graph initiative, large amount of owl:sameAs links need to be established. Most of the existing entity alignment methods are based on the matching progress of schema pattern, and there are limitations in...
Hydrocracking process is a complex long-running industrial process. The change of inlet conditions will result in fluctuation of operating parameters and change of running state. It is necessary to classify the inlet conditions to detect the change of raw materials timely, so that the subsequent global operation conditions can be analyzed. However, sampling analysis of the quality indexes of raw oil...
Load profiling refers to a procedure which leads to the formulation of daily load curve and consumer classes regarding the similarity of the curves shapes. This procedure incorporates a set of unsupervised machine learning algorithms. Various researches propose clustering algorithms for grouping together load curves with high degree of similarity. K-means is the most common algorithm in the load profiling...
The study of flower classification system is a very important subject in the field of Botany. A classifier of flowers with high accuracy will also bring a lot of fun to people's lives. However, because of the complex background of flowers, the similarity between the different species of flowers, and the differences among the same species of flowers, there are still some challenges in the recognition...
In this paper, we present fusion and classification process of change indices using multitemporal satellites images in the aim to detect the change of surface states after a flood. This process is performed in the framework of Dempster Shafer Theory (DST), which takes into account the imprecision and the ignorance related to data. We apply this process to a study site located at south west of England,...
While creating contemporary management systems and automating technology processes and objects, there are different methods of signal processing based on computer and information technologies that can be employed. An important research direction when creating the systems is the research direction of the reliability and assessment of technical condition of various objects in the industrial engineering...
Link prediction is to calculate the probability of a potential link between a pair of unlinked nodes in the future. It has significance value in both theoretical and practical. The similarity of two nodes in the networks is an essential factor to determine the probability of a potential link between them. One of the important methods with the similarity of two nodes is to consider common neighbors...
Forest disturbances caused by Pantana phyllostachysae caused the death of extensive bamboos in Hubei province, China in 2015. Field survey is time-consuming and at higher cost to satisfy the forest management requirements. Satellite remote sensing technology having the characteristics of landscape of coverage, convenient, and fast in formation acquisition, is one of the most important and most effective...
Automatic text classification is the key technology to process and organize large-scale text data. It is well known that the high dimensionality of feature space is a main challenge for text classification. In order to attenuate such a problem as well as inspired by existing arts, we propose an effective text feature selection algorithm by novelly fusing the classical methodologies of Gini index and...
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