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Research And Development Of Granular Neural Networks, Hui Li, Shifei Ding
Research And Development Of Granular Neural Networks, Hui Li, Shifei Ding
Applied Mathematics & Information Sciences
Granular neural networks(GNNs) as a new calculation system structure based on Granular Computing(GrC) and artificial neural network can be able to deal with all kinds of granular information of the real world. This article has made the summary on the development and the present situation of GNNs. Firstly, it introduces the basic model of GrC: word calculation model based on fuzzy sets theory, rough sets model, granular computing model based on quotient space theory and so on, summarizes the research progress of fuzzy neural networks(FNNs) and rough neural networks(RNNs), then analyses the ensemble-based methods of GNNs, researches their meeting point …
Forecasting Model Of Coal Mine Water Inrush Based On Extreme Learning Machine, Zuopeng Zhao, Pei Li, Xinzheng Xu
Forecasting Model Of Coal Mine Water Inrush Based On Extreme Learning Machine, Zuopeng Zhao, Pei Li, Xinzheng Xu
Applied Mathematics & Information Sciences
In order to satisfy the real-time requirement of the coal mine water inrush, comprehensively considering the master influencing factors filtered out by using principal component analysis (PCA) of coal mine water inrush, a forecasting model of coal mine water inrush based on extreme learning machine (ELM) is proposed in this paper by combining with the characteristics of single hidden layer feedforward networks (SLFNs). The model is used to test the samples, and then compare the experimental results of ELM with back-propagation (BP) and support vector machine (SVM). The experimental results show that, compared with BP and SVM, this method is …
A Simple Way To Reconstruct The Wigner Function, H. Manuel Moya-Cessa, D. N. Christodoulides
A Simple Way To Reconstruct The Wigner Function, H. Manuel Moya-Cessa, D. N. Christodoulides
Applied Mathematics & Information Sciences
We show a simple mechanism to measure the Wigner function of a harmonic oscillator. For this system we also show that autocorrelation and Wigner functions are equivalent.
A Rational And Efficient Algorithm For View Revision In Databases, R. Delhibabu, G. Lakemeyer
A Rational And Efficient Algorithm For View Revision In Databases, R. Delhibabu, G. Lakemeyer
Applied Mathematics & Information Sciences
The dynamics of belief and knowledge is one of the major components of any autonomous system that should be able to incorporate new pieces of information. In this paper, we argue that to apply rationality result of belief dynamics theory to various practical problems, it should be generalized in two respects: first of all, it should allow a certain part of belief to be declared as immutable; and second, the belief state need not be deductively closed. Such a generalization of belief dynamics, referred to as base dynamics, is presented, along with the concept of a generalized revision algorithm for …
On The Dynamics Of A 4d Local Cournot Model, Juan Luis Garc?A Guirao, Marek Lampart, Guo Hua Zhang
On The Dynamics Of A 4d Local Cournot Model, Juan Luis Garc?A Guirao, Marek Lampart, Guo Hua Zhang
Applied Mathematics & Information Sciences
The aim of this paper is to analyze the dynamics of a four dimensional system described in [Appl. Math. Let., 23, 836-838, (2010)], which generalizes the classical Cournot competition in a local way. In particular, by considering an aggregation parameter of production costs, we are able to describe for some ranges of the parameter: the periodic structure, the asymptotic dynamics and the chaotic properties of the system via the study of its topological entropy and the Li and Yorke chaos.
Hybrid Seeker Optimization Algorithm For Global Optimization, Milan Tuba, Ivona Brajevic, Raka Jovanovic
Hybrid Seeker Optimization Algorithm For Global Optimization, Milan Tuba, Ivona Brajevic, Raka Jovanovic
Applied Mathematics & Information Sciences
Swarm intelligence algorithms have been succesfully applied to hard optimization problems. Seeker optimization algorithm is one of the latest members of that class of metaheuristics and it has not yet been thorougly researched. Since the early versions of this algorithm were less succesful with multimodal functions, we propose in this paper hybridization of the seeker optimization algorithm with the well known artificial bee colony (ABC) algorithm. At certain stages we modify seeker’s position by search formulas from the ABC algorithm and also modify the inter-subpopulation learning phase by using the binomial crossover operator. Our proposed algorithm was tested on the …
Conservation Laws Of The Bretherton Equation, A. H. Kara, Houria Triki, Anjan Biswas
Conservation Laws Of The Bretherton Equation, A. H. Kara, Houria Triki, Anjan Biswas
Applied Mathematics & Information Sciences
This paper obtains the conservation laws of the Bretherton equation that is considered with dual-power law nonlinearity. The multiplier approach is used to extract several conserved densities of this equation. Finally, the conserved quantities are computed by using the 1-soliton solution that has been obtained earlier.
Some Iterative Schemes For Solving Extended General Quasi Variational Inequalities, Muhammad Aslam Noor, Khalida Inayat Noor, Awais Gul Khan
Some Iterative Schemes For Solving Extended General Quasi Variational Inequalities, Muhammad Aslam Noor, Khalida Inayat Noor, Awais Gul Khan
Applied Mathematics & Information Sciences
In this paper, we consider a new class of quasi variational inequalities involving three operators, which is called the extended general quasi variational inequality. It is shown that the extended general quasi variational inequalities are equivalent to the fixed problems. This equivalence is used to suggest and analyze some iterative methods for solving the extended general quasi variational inequalities. Convergence analysis is also considered. We have also shown that the extended general quasi variational inequalities are equivalent to the extended general implicit Wiener-Hopf equations. This alternative formulation is used to suggest and analyze some iterative methods. The convergence analysis of …
Research Of Individual Neural Network Generation And Ensemble Algorithm Based On Quotient Space Granularity Clustering, Li Hui, Ding Shifei
Research Of Individual Neural Network Generation And Ensemble Algorithm Based On Quotient Space Granularity Clustering, Li Hui, Ding Shifei
Applied Mathematics & Information Sciences
The aim of this paper is to develop an individual neural network generation and ensemble algorithm based on quotient space granularity clustering. Firstly, we give the characteristics of the quotient space granularity and affinity propagation(AP) clustering. Secondly, we introduce the quotient space concept to the AP clustering analysis, which can find an optimal granularity from all possible granularities. Then using improved AP clustering algorithm to seek optimal results of sample clustering and using different individual neural network to learn different categories of samples so that the degree of difference between networks and the generalization ability of neural network ensemble(NNE) can …
An Improved Discriminative Tracking Algorithm Based On Spatial Information And Model Updating, Liangwei Jiang, Jiang Jiang, Nong Sang
An Improved Discriminative Tracking Algorithm Based On Spatial Information And Model Updating, Liangwei Jiang, Jiang Jiang, Nong Sang
Applied Mathematics & Information Sciences
Tracking object occluded partially is a difficult problem in video surveillance. Many previous tracking methods fail to track occlusion objects robustly. In this paper, we propose an improved discriminative tracking algorithm based on bag of patches to cope with the partial occlusion as well as drift. In the proposed method, the spatial information is introduced to build the object appearance model and construct the confidence map from three different aspects, which directly determine the ultimate tracking effect. In addition, the context information of the small image patches is also applied. In order to adapt to the variance of the environment, …
Domain Knowledge Blended Affinity Propagation, Wei Chen, Qichong Tian, Xiaorong Jiang, Zhibo Tang, Caihua Guo, Xinzheng Xu
Domain Knowledge Blended Affinity Propagation, Wei Chen, Qichong Tian, Xiaorong Jiang, Zhibo Tang, Caihua Guo, Xinzheng Xu
Applied Mathematics & Information Sciences
As an important clustering algorithm, Affinity Propagation (AP) algorithm can quickly find the reasonable clustering center. But the AP algorithm is difficult to make correct clustering, when the sample in the weaker separability feature space. In this paper, the Domain Knowledge Blended Affinity Propagation (DKB-AP) algorithm is proposed. Combining the domain knowledge function and the similarity measure of the AP algorithm, the algorithm makes iterating to obtain the clustering result. The experimental data are three random sample sets, including two sample sets whose subclass aggregation degree are good, one sample set whose subclass aggregation degree is weak. The clustering results, …
Research On Transaction Web Service Selection Algorithm In Wsc, Hu Jingjing, Zhao Xing, Cao Yuanda
Research On Transaction Web Service Selection Algorithm In Wsc, Hu Jingjing, Zhao Xing, Cao Yuanda
Applied Mathematics & Information Sciences
Web service composition (WSC) needs transactional support to guarantee its consistent and reliable execution. To improve the validity of service selection, a transaction service composition model (TSM) is proposed. The model associates the quality of service (QoS) with dependencies between transactional states and time. Based on the model, a parallel algorithmłłtransaction QoS selection algorithm (TQSA) is developed, which combines genetic algorithm (GA) and service compensation computing, and can be applied to dynamic service composition due to its mechanism of selection and evaluation performing at the same time. To improve the success of composition, an algorithm I-TQSA is further developed by …
An Extension Of A New Kind Of Graphics Fitting Method, Shaohui Deng, Sujie Guan, Guozhao Wang, Shaobo Deng
An Extension Of A New Kind Of Graphics Fitting Method, Shaohui Deng, Sujie Guan, Guozhao Wang, Shaobo Deng
Applied Mathematics & Information Sciences
The progressive iterative approximation method (PIA) for fitting is developed in recent years. The previous research is mainly restricted to the normalized totally positive (NTP) basis. In this paper, we propose a new extended method which can unify the classic PIA method, weighted PIA method (WPIA) and local PIA (LPIA) method into one formula by introducing the transform matrix. In addition, the method presented by us has the following advantages: firstly, it can be applied to any basis; secondly, compared with other extended methods, the convergence rate of our method can be independent of the initial parameterizations; thirdly, for the …
Research On Color Consistency For Color Marketing In Electronic Business System, Xinwu Li
Research On Color Consistency For Color Marketing In Electronic Business System, Xinwu Li
Applied Mathematics & Information Sciences
Color consistency for color marketing in electronic business system is one of important factors for online customers to choose products, so it is the key techniques to guarantee color consistency when color image transmit and converse among different color reproduction image devices in electronic business system. The paper, taking scanned input image for examples, advances a new color management model to keep color consistency through analyzing color rendering principle of scanners. First the parameters of Yule-Nielson equation are reinterpreted, making them can be used for non-printing dot image which only can be used for printing dot image originally; Second, standard …
A Novel Discrete Cuckoo Search Algorithm For Spherical Traveling Salesman Problem, Xinxin Ouyang, Yongquan Zhou, Qifang Luo, Huan Chen
A Novel Discrete Cuckoo Search Algorithm For Spherical Traveling Salesman Problem, Xinxin Ouyang, Yongquan Zhou, Qifang Luo, Huan Chen
Applied Mathematics & Information Sciences
In this paper, we propose a novel discrete cuckoo search algorithm (DCS) for solving spherical Traveling Salesman Problem (TSP) where all points are on the surface of a sphere. The algorithm is based on the L´evy flight behaviour and brood parasitic behaviour. The proposed algorithm applies study operator, the ”A” operator, and 3-opt operator to solutions in the bulletin board to speed up the convergence. Optimization results obtained for HA30 (an instance from TSPLIB) and different size problems are solved. Compared with GA, DCS is better and faster.
An Undetachable Threshold Digital Signature Scheme Based On Conic Curves, Yang Shi, Guoyue Xiong
An Undetachable Threshold Digital Signature Scheme Based On Conic Curves, Yang Shi, Guoyue Xiong
Applied Mathematics & Information Sciences
Based on analysis of security problems on malicious hosts, a special undetachable threshold digital signature scheme is proposed. This scheme uses a cryptosystem based on conic curves and achieves the most important security characteristic of protecting mobile agents against malicious hosts, i.e., undetachablility. Furthermore, this scheme solves the case where a host can force an agent to commit to a sub-optimal transaction. Computational studies show that this scheme is superior to the RSA-based undetachable threshold digital signature scheme.
A Modified Runge-Kutta-Nystr?M Method By Using Phase Lag Properties For The Numerical Solution Of Orbital Problems, Dimitris F. Papadopoulos, T.E. Simos
A Modified Runge-Kutta-Nystr?M Method By Using Phase Lag Properties For The Numerical Solution Of Orbital Problems, Dimitris F. Papadopoulos, T.E. Simos
Applied Mathematics & Information Sciences
In this paper, a new modified Runge-Kutta-Nystr¨om method of third algebraic order is developed. The new modified RKN method has phase-lag and amplification error of order infinity, also the first derivative of the phase lag is of order infinity. Numerical results indicate that the new method presented in this paper, is much more efficient than other methods of the same algebraic order, for the numerical integration of orbital problems.
Implementing Sparse Matrix-Vector Multiplication With Qcsr On Gpu, Jilin Zhang, Enyi Liu, Jian Wan, Yongjian Ren, Miao Yue, Jue Wang
Implementing Sparse Matrix-Vector Multiplication With Qcsr On Gpu, Jilin Zhang, Enyi Liu, Jian Wan, Yongjian Ren, Miao Yue, Jue Wang
Applied Mathematics & Information Sciences
We are going through the computation from single core to multicore architecture in parallel programming. Graphics Processor Units (GPUs) have recently emerged as outstanding platforms for data parallel applications with regular data access patterns. However, it is still challenging to optimize computations with irregular data access patterns like sparse matrix-vector multiplication (SPMV). SPMV is one of the most important computational kernels in engineering practice and scientific computation. Various data formats to store the sparse matrix have been implemented on GPUs to maximize the performance. In this paper, we propose and evaluate a new implementation of SPMV on GPU based on …
Defect Detection Of Smt Electronic Modules, Xibing Li, Jianjia Wang
Defect Detection Of Smt Electronic Modules, Xibing Li, Jianjia Wang
Applied Mathematics & Information Sciences
To automatically detect SMT (surface mount technology) electronic modules, algorithms are investigated for geometry and shape features, module matching and detection in PCB (printed-circuit board) components. First, geometry and shape features of SMT electronic modules are presented. Then matching technology and process for SMT electronic modules are studied through optimization searching algorithms, such as similarity based detection and pyramid algorithms. Based on the analysis of major defects, algorithms for detecting major defects in SMT electronic modules are investigated. Finally, the crucial factors affecting inspection precision and speed, i.e., components contour, searching range and minimum similarity, are analyzed. The experimental results …
Parallel Catmull-Rom Spline Interpolation Algorithm For Image Zooming Based On Cuda, Tunhua Wu, Baogang Bai, Ping Wang
Parallel Catmull-Rom Spline Interpolation Algorithm For Image Zooming Based On Cuda, Tunhua Wu, Baogang Bai, Ping Wang
Applied Mathematics & Information Sciences
In order to scale video image real-timely, a GPU-aided parallel interpolation algorithm was proposed. Catmull-Rom Spline algorithm for image zooming was reformed into SIMD (Single instruction, multiple data) mode according to CUDA programming model. Re-sampling of each pixel was completed by a GPU thread. Hence, time-consuming re-sampling procedure of the whole zooming process were handled by parallel threads. The proposed algorithm runs hundreds times faster than traditional algorithm in experiments, and the speed is fast enough for scaling video frames real-timely. In addition, this algorithm can be extended to solve many other image processing related problems, such as image denosing …
A Low Papr Visible Light Communication System Employing Sc-Fdma Technique, Young-Ju Kim, Xun Li
A Low Papr Visible Light Communication System Employing Sc-Fdma Technique, Young-Ju Kim, Xun Li
Applied Mathematics & Information Sciences
White light emitting diode (WLED) technology has been regarded as an environment-friendly lighting in the future. The WLED lighting system is able to provide short range wireless communication while illuminating rooms. The WLED based visible light communication (VLC) systems employing orthogonal frequency division multiplexing access (OFDMA) technique has been investigated in many researches. However, the OFDMA technique has the inherent high peak-to-average power ratio (PAPR). Such a VLC system with high peak power produces flickering light that can be detected by human eyes uncomfortably. In this paper, the application of single carrier frequency division multiplexing access (SC-FDMA) to VLC system …
Wipad: An Automatic Monitoring System With Wireless Network Based On Image Processing For Harvest Disease, Mingming Xiao
Wipad: An Automatic Monitoring System With Wireless Network Based On Image Processing For Harvest Disease, Mingming Xiao
Applied Mathematics & Information Sciences
In this system, an intelligent monitoring system for crop is implemented. It comprises various function modules. The kernel one is the automatic identification module of the plant diseases and pests. The feature of pre-processing is first carried out to generate the various feature vectors, and then a SVM classifier is trained from these vectors. The experimental results firmly demonstrate the discriminating function of the SVM classifier.
Study On Influence Factors Of Nonlinear Finite Element Analysis For High Arch Dams, Xiaoqing Liu, Tongchun Li, Zhiqiang Wang, Lanhao Zhao
Study On Influence Factors Of Nonlinear Finite Element Analysis For High Arch Dams, Xiaoqing Liu, Tongchun Li, Zhiqiang Wang, Lanhao Zhao
Applied Mathematics & Information Sciences
In communication network, WDM optical backbone network has become the primary long-distance options. In this paper, the structure of WDM optical networks are analyzed, the add-drop system in the architecture of WDM optical networks is discussed. In order to improve network efficiency, we analyzed the characteristics of network routing, and proposed a new routing design method. In communication network, a good routing is very important for network operation. Routing technologies manage the flow of data between network segments in optical communication network. In addition, we also discussed the WDM optical network switching technology.
Segmentation Of Cerebral Edema Around Spontaneous Intracerebral Hemorrhage, Mingyang Chen, Qingmao Hu, Zhenchuan Liu, Shoujun Zhou, Xiaodong Li
Segmentation Of Cerebral Edema Around Spontaneous Intracerebral Hemorrhage, Mingyang Chen, Qingmao Hu, Zhenchuan Liu, Shoujun Zhou, Xiaodong Li
Applied Mathematics & Information Sciences
An automatic method is presented to extract edema around spontaneous intracerebral hemorrhage (SICH). A new way to cluster edema based on region growing is proposed, with seeds derived from expectation-maximization algorithm, local grayscale mean derived from adaptive local thresholding with varied window sizes, and growing rules that combines local grayscale mean and grayscale information in the form of two-dimensional entropy. The algorithm has been validated on 36 patient datasets to achieve a Dice coefficient of 0.79 in less than 3 minutes. It may provide a potential tool for neurosurgeons to quantify edema and guide therapy of patients with SICH.
Correlation Function And Business Cycle Turning Points: A Comparison With Markov Switching Approach, I. Medhioub, H. Eleuch
Correlation Function And Business Cycle Turning Points: A Comparison With Markov Switching Approach, I. Medhioub, H. Eleuch
Applied Mathematics & Information Sciences
We present a new technical approach based on the autocorrelation function, widely used in physics, to determine and to analyze the business cycle turning points of an economic activity. This method is adapted to stochastic processes and does not require a smoothing technique. The application of this method to the industrial production seasonally adjusted of Tunisia, for the period 1994:4 –2006:8 gives similar results to these obtained by two-state Markov switching model.
Multi-Modal Emotion Recognition Fusing Video And Audio, Chao Xu, Pufeng Du, Zhiyong Feng, Zhaopeng Meng, Tianyi Cao, Caichao Dong
Multi-Modal Emotion Recognition Fusing Video And Audio, Chao Xu, Pufeng Du, Zhiyong Feng, Zhaopeng Meng, Tianyi Cao, Caichao Dong
Applied Mathematics & Information Sciences
Emotion plays an important role in human communications. We construct a framework for multi-modal fusion emotion recognition. Facial expression features and speech features are respectively extracted from image sequences and speech signals. In order to locate and track facial feature points, we construct an Active Appearance Model for facial images with all kinds of expressions. Facial Animation Parameters are calculated from motions of facial feature points as expression features. We extract short-term mean energy, fundamental frequency and formant frequencies from each frame as speech features. An emotion classifier is designed to fuse facial expression and speech based on Hidden Markov …
Towards Qos Prediction For Web Services Based On Adjusted Euclidean Distances, Yuyu Yin, Dongjing Yu, Ying Li
Towards Qos Prediction For Web Services Based On Adjusted Euclidean Distances, Yuyu Yin, Dongjing Yu, Ying Li
Applied Mathematics & Information Sciences
QoS-based service selection is an important issue of service-oriented computing (SOC). A common premise of previous research is that the QoS values of services to target users are supposed all known. However, the real situation is that many of them may be missing. In this paper, we propose an enhanced CF-based QoS prediction approach to predict such missing values. Compared with existing QoS prediction methods, our proposed one has three new features: 1) adding a data normalization process to remove the impact of different QoS scale; 2) using the adjusted Euclidean Distances equation for similarity calculation to improve the prediction …
Improved Accuracy Of Linear Multistep Methods, Samir Karaa
Improved Accuracy Of Linear Multistep Methods, Samir Karaa
Applied Mathematics & Information Sciences
We present a technique for improving the accuracy of a given multistep method. We first propose a new formulation of the θ-method providing a general framework for studying stability and allowing to select the appropriate values of the parameter θ that increase the order of accuracy. The idea is followed through to generate optimal linear multistep methods.
Multichannel Arma Signal Covariance Intersection Fusion Wiener Filter For The Two-Sensor System With Time-Delayed Measurements, Peng Zhang, Zili Deng
Multichannel Arma Signal Covariance Intersection Fusion Wiener Filter For The Two-Sensor System With Time-Delayed Measurements, Peng Zhang, Zili Deng
Applied Mathematics & Information Sciences
For the two-sensor, multi-channel autoregressive moving average (ARMA) signals with measurement delays, the system with measurement delays is converted into the system without measurement delays by the measurement transformation method. When the filtering error cross-covariances are known, by the Kalman filtering method, based on the white noise Wiener filters and measurement Wiener predictors, the optimal fusion Wiener signal filters weighted by matrices, diagonal matrices and scalars are presented. When the filtering error cross-covariances are unknown, by the covariance intersection (CI) fusion method, the CI fusionWiener signal filter is presented. It is rigorously proven that the actual accuracy of the CI …
On The Moduli Space Of Smooth Plane Quartic Curves With A Sextactic Point, Alwaleed Kamel, M. Farahat
On The Moduli Space Of Smooth Plane Quartic Curves With A Sextactic Point, Alwaleed Kamel, M. Farahat
Applied Mathematics & Information Sciences
Let Mg be the moduli space of smooth algebraic curves of genus g over C. In this paper, we prove that the set Sr⊆ M3 of moduli points of smooth plane quartic curves (nonhyperelliptic curves of genus 3) having at least one sextactic point of sextact multiplicity r, where r ∈ {1, 2, 3}, is an irreducible, closed and rational subvariety of codimensional r − 1 of M3 − H3 (where H3 ⊂ M3 is the hyperelliptic locus ).