Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
In this paper, based on investigating and analyzing on the affecting factors for support type of development roadways as well as the successful support cases in Chengchao Iron mine, the improved BP neural network is put forward to study on the support type of development roadways. It may be seen from the learning course of learning samples and the prediction results of support types that whether the...
In this paper, the author converts inequality constrained optimization problem into equality constrained optimization problem by using slack variables. Then we construct a new multiplier penalty function using the penalty function who belongs to equality constraints and was raised by Bertskas in 1982.
As an effective global search method, genetic algorithm has obvious advantages. But it usually has problems of premature convergence and local optimum in practical application. According to this, a new algorithm with improved selection, crossover and mutation is proposed. Through the simulation experiments, the improved algorithm shows its faster convergence and better stability. It is valid which...
In this paper the operation of a recently introduced novel version of the popular “Model Reference Adaptive Controller (MRAC)” is compared with that of a simple version of its possible traditional implementations. The “traditional implementations” normally use Lyapunov's 2nd (“direct”) method for adaptive tuning of the controllers' parameters. This method yields global asymptotic stability but its...
An on-line BSE algorithm with an adaptive learning rate is proposed. By indirectly studying one of the existing on-line BSE algorithms based on line predictability, the bound for the optimal learning rate which guarantees the convergence of the algorithm is derived. Based on the analysis results, an on-line algorithm with an adaptive learning rate is presented. Since the learning rates of the existing...
Gaussian mixture model is a commonly used background modeling method in moving object detection. Gaussian mixture model has a strong adaptivity to various complicated backgrounds, but converges slowly and lacks shadow detection capability. In this paper, we propose an improved Gaussian mixture model which models background and foreground at the same time, accelerates convergence when moving objects...
The social cognitive optimization algorithm is one of the newest intelligent algorithms, and this algorithm can help the solvers to avoid tripping in local optimization when solving the nonlinear constraint problems effectively. The algorithm is based on the social cognitive theory and the key point of the ergodicity is the process of refreshing the knowledge points. Modified and optimized the conditions...
In view of shortcomings such as premature convergence and oscillation in Simple Genetic Algorithms (SGA), the article adopts the method of adaptive adjusting for the probabilities of crossover and mutation. So the Improved Genetic Algorithms (IGA) is formed by adding the transgenic operator to SGA. And the optimum design program of steel box-concrete composite arch bridge based on improved genetic...
This paper investigates the stabilization problem for networked control systems (NCSs) with limited data rates over an additive white Gaussian noise (AWGN) channel. The notion of control with limited data rates means specifying the lower bound of data rates, above which there exists a coding and control scheme for stabilization of linear time-invariant systems. Different from the literatures, the...
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expectation maximization (EM) methodology. The key feature of our approach is related to a top-down hierarchical search for the number of components, together with the integration of the model selection criterion within a modified...
When a local optimal solution is reached with classical Particle Swarm Optimization (PSO), all particles in the swarm gather around it, and escaping from this local optima becomes difficult. To avoid premature convergence of PSO, we present in this paper a novel variant of PSO algorithm, called MPSOM, that uses Metropolis equation to update local best solutions (lbest) of each particle and uses mutation...
Advantages of None Euclidean Relational Fuzzy C-means (NERFCM) is analysed, by which four Fuzzy C-means (FCM) clustering algorithms are compared, which includes Fuzzy C-means (FCM) and traditional Relational Fuzzy C-means (RFCM) and None Euclidean Relational Fuzzy C-means (NERFCM) and Any Relational Fuzzy C-means (ARFCM). Their common points and different limitations on usage are discussed, finally...
Particle swarm optimization (PSO) is a new swarm intelligence algorithm, derived from artificial life and evolutionary computation theory. It makes full use of the information-sharing particles of the cluster to obtain the optimal solution of the evolution from disorder to orderliness. It has received great concern because of its simple calculation forms, parameter settings and a good convergence...
This paper proposes three methods for combining various probabilistic models for retrieving answers from community-based question answering (cQA) archives. We adopt four probabilistic models for these combinations, i.e., (1) the language model measuring similarity between a query and a question stored in the cQA archive, (2) two translation models for measuring the similarity between a query and an...
In this paper, we propose an improved active contour model to detect pedestrian in video sequences. Our method can detect pedestrian whose profiles are constantly changing when they are walking. First, we improve the internal energy computation by using the squares of the distance between average distance of all adjacent points in the contour curve and the control points, and construct local energy...
K-Means algorithm is one of the most used clustering algorithm for Knowledge Discovery in Data Mining. Seed based K-Means is the integration of a small set of labeled data (called seeds) to the K-Means algorithm to improve its performances and overcome its sensitivity to initial centers. These centers are, most of the time, generated at random or they are assumed to be available for each cluster....
The compressible miscible displacement in a porous media is considered in this paper. The concentration is treated by a characteristics collocation method, and the pressure is treated by an orthogonal collocation method. Optimal order estimates in L2-norm and numerical experiment are derived.
In this paper we discuss different Subtracters design based on quantum dot cellular automata (QCA). QCA is an emerging nanotechnology for electronic circuits. It has the potential for attractive features such as faster speed, smaller size and low power consumption than transistor based technology. By taking the advantages of QCA we are able to design interesting computational architectures. The Subtracters:...
One of the main obstacles to reliable communications is the inter symbol interference. An adaptive equalizer is required at the receiver to mitigate the effects of non-ideal channel characteristics and to obtain reliable data transmission. The conventional way to combat with ISI is to include an equalizer in the receiver. This paper presents a new approach to equalization of communication channels...
In linear space, the classical perceptron algorithm is simple and practical. But when concerning the nonlinear space it is severely confined mainly on its signal layer structure. This paper analyzes the geometry characteristic of solve region in the pattern set, and presents a new algorithm based on the solve region. The new algorithm could find the better solve vector in the solve region on condition...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.