Papers by Keyword: Information Entropy

Abstract: This paper presents a model of a thin film formation process of an amorphous alloy as a sequential procedure when a conditional unit of substance is randomly thrown onto a substrate at each next step. The islands of a precipitant are generated on the substrate with an increase of number of steps (density defects of substance). We determine the probability distribution of an island area, which shows the maximum informational entropy. An algorithm for computing estimates of parameters of this distribution is obtained. The results of processing experimental data are presented. We demonstrate that the proposed distribution is more consistent with the experimental data than the Pareto distribution.

Abstract: The equipment operational reliability evaluation is very important for working safely. The traditional reliability evaluation methods couldn’t meet the demands. In order to consider the detection information during the operation from devices, the operational reliability assessment method based on information entropy and empirical mode decomposition (EMD) is proposed. First, the equipment operation detected signals’ multiple intrinsic mode functions (IMF) are obtained by using EMD ; then the relative energy of each intrinsic mode functions are calculated and their information entropy are normalized. Finally the operational reliability of equipment operating status can be judged according to the normalization information entropy value. The method is used for a rotor test analysis considering of the degree of injury. The results demonstrated the method effectively, which provided an effective method for assessing the running reliability of mechanical equipment with less sample data.

Abstract: In order to improve the diagnosis efficiency of faulty circuits with tolerance and to ameliorate characteristic description of faulty symptom, the faulty features of the circuit with tolerance are created by information entropy method at first, and then feature extraction method based on discrete Particle Swarm Optimization algorithm (PSO) is proposed to obtain the optimal feature subset of faulty feature. At last, the optimal feature subset is used to train the classifier to diagnosis the faults of the circuit with tolerance. Experiments results show the validity of this proposed method.

Abstract: Evaluating motion similarity between trainer and trainee is a key part in computer-assisted sports teaching system. Our similarity evaluation algorithm mainly contains four steps. Firstly, the multichannel 3D human motion data are captured using the Kinect, a depth sensor of Microsoft. Next, in order to greatly reduce the amount of data analysis, the piecewise extremum method (PEM) is applied to achieve this goal. Then, considering that doing the same motions the rhythms of different people are not synchronized, the Dynamic Time Warping algorithm (DTW) is selected to solve the problem of analyzing one channel unequal length motion sequences. Finally, the similarity between the two sets of multichannel human motion sequences can be evaluated using the combined method of the information entropy and DTW. The experimental results indicate that compared with other traditional methods, the proposed method not only accurately measures similarity degree of different motions, but also requires less computational time and memory storage capacity.

Abstract: For reasons of low accuracy of traditional leakage, a pipeline leakage diagnosis method based on multi-weight neural networks is presented to recognized leak signal in city gas pipelines. By using analysis and modeling a multi-weight neural networks are established at normal node to simplify network structure. The Information entropy of leakage characteristic parameters of negative pressure wave was used as input eigenvector respectively for primary diagnosis. It has been applied for leakage diagnosis in city gas pipelines with the whole computational process done by a computer. Results of simulation and tests show that this method has its advantage in dealing with multi-coupled fault situations and is featured by a high probability of accuracy, which not only proves the method to be effective, but also provides a theoretical basis and a new way for leak diagnosis of other pipelines.

Abstract: Traditional reservoir operation is mainly for flood control and promoting benefits, which ecological factors are not fully considered in. This would probably lead to degradation of river ecosystem. In order to alleviate the influence of reservoirs on river ecosystem, a multi-objective ecological operation model for reservoirs was established. Then, a novel approach was proposed to solve the multi-objective model, which combined a multi-objective particle swarm optimization (MOPSO) algorithm with the non-dominated solutions evaluation approach. MOPSO algorithm was introduced to generate a set of Pareto-optimal solutions, while the non-dominated solutions evaluation approach, based on k-means clustering and the information entropy method, was adopted to provide an alternative sequence for a set of Pareto-optimal solutions. Finally, the proposed approach was applied to the ecological operation of the reservoirs at the main stream of Xiuhe river in Poyang Lake basin in China. The results show that the proposed approach is able to offer the quantifiable benefits or costs among different objectives for the reservoir operators, and can provide a useful tool for decision makers to solve multi-objective water resources and hydrology problems.

Abstract: The basic idea of safety region is introduced into roller bearing condition monitoring. Power Spectral Entropy, Singular value Entropy are used comprehensively for the estimation of the safety region and the identification of normal state and faulty state for the roller bearing operational status. First, the vibration acceleration data was segmented according to a certain time interval and then establish Power Spectral Entropy, Singular value Entropy as characteristics of roller bearings. Finally, SVM was used for the estimation of the safety region of the roller bearing operation state, and multi-class SVM was used of the identification of the four states. The results show that both the safety region estimation and state identification are accurate, and confirm the validity of the method.

Abstract: Disparity estimation is used to eliminate redund ancy among different views in multiview video coding in order to obtain high compression efficiency. This paper proposes a reference viewpoint selection method based on the judgment principle of block feature vectors and similarities, which can reduce complexity and increase coding performance under the premise that the coding quality is ensured. Experimental results have demonstrated the effectiveness of this algorithm.

Abstract: Screening candidates is the key step to improve the efficiency of ontology mapping. Minimum spanning tree clustering is one of the important ways of graph clustering algorithm. Defining the related concepts and methods first, according to the characteristics of the ontology file itself, Select graph clustering of minimum spanning tree clustering algorithm, To screening candidates of participate in the concept of mapping, Aiming at the deficiency and improvement of objective function in the algorithm, based on the system information entropy instead of the complicated calculation of similarity to supervise the clustering. To reduce the computational scale and improve the efficiency.

Abstract: Water allocation is a very complex problem, involving social, economic, environmental, and political factors. Consequently, it is a multi-objective decision-making problem. This paper presents a multi-objective model for the optimal allocation on multisource water for multiuser under sufficiently considering the harmonious development among economy, society and environment. A multi-objective particle swarm optimization (MOPSO) algorithm is employed to generate a set of Pareto-optimal solutions. At the same time, to facilitate easy implementation for the water allocation operator, information entropy theory is adopted to sort the decision results according to the magnitude of the superiority degrees. As a case study the proposed approach has been applied to the reasonable allocation of water supply and demand in the water-receiving areas of the South-to-North Water Transfer Project in China, in which the maximal benefit of economy, society and environment was regarded as the multi-objectives. The results show that the proposed approach is able to offer the quantifiable benefits or costs among different objectives for the water managers, and is highly professional in making decisions for allocating water among use sectors and different areas.