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In this paper, passive localization from a single satellite is addressed. Passive localization is a typical nonlinear filtering and optimal estimation problem, and usually suffers large initial estimation error and low observability. When localizing an emitter located at the surface of the earth, the localization problem needs to satisfy the constraint condition of the earth surface. Particle swarm...
In this research, we propose a machine learning system based on Particle Swarm Optimization (PSO) and Support Vector Machines (SVM) for stock market forecast. A variety of indicators from the technical analysis field of study are used as input features. We also make use of the correlation between stock prices of different companies to forecast the price of a stock, making use of technical indicators...
This paper describes the outlier data mining and commonly used outlier mining methods, on this basis, it presents an outlier mining algorithm based on particle swarm and subspace, and then the experiments show that the algorithm does not rely on user input parameters, has strong flexibility and high operational efficiency. Finally this paper designs an outlier mining system based on subspace, in detail...
In order to improve the convergent speed and raise the accurate level of solutions further, in this study, we present a novel particle swarm optimizer, called Particle Swarm Optimizer with randomized quasi-random initialization and general recognition. The proposed algorithm uses Quasi-random sequence to initialize the population for a more uniform population distribution. Cauchy distribution and...
For the complex nonlinear systems, a self-adaptive modeling method based on T-S fuzzy RBF NN is introduced in this paper, in which online fuzzy clustering and improved PSO algorithms are used to implement the structure identification and parameter identification of the network. After theory analysis, the corresponding computer simulation was done to confirm the effectiveness and superiority of the...
Particle swarm optimization (PSO) is a new evolution computing technology, its applications in discrete problem is a hot and valued field. Basing on the present algorithm of particle swarm optimization, this paper construct a special mixed discrete particle swarm optimization (MDPSO), and get a new formula of the velocity, via presenting the crossover and mutation of the genetic algorithm (GA). As...
According to the model of distribution center location, this paper establishes a SA-PSO algorithm, which combines the particle swarm optimization algorithm and simulated annealing. Using a mixed binary and floating-point coding method to avoid increasing scale complexity, the algorithm improves particle swarm optimization algorithm which is very easy to get in trouble with local extremum, also it...
A local outlier mining algorithm is put forward based on the partition of subspaces. The algorithm first divides the data set into disjoint subspaces, using the degree of skewness to measure the pros and cons of the space division, and adopting the particle swarm optimization algorithm to search the optimal partition of subspaces set; then aiming at each optimal partition of subspaces to calculate...
This paper introduces the application of particle swarm optimization(PSO) algorithm. Based on the analysis of the characteristics of the sustainable development indexes, this paper adopts the classified individual sustainable development index formula and the composite index formula, optimizes the model parameters by PSO algorithm, and sets up a composite index evaluation model of sustainable development.
Message-Passing is the main decoding algorithm for Low-Density Parity Check (LDPC) Codes, in which Logarithmic Belief Propagation (Log-BP) algorithm is the most popularly used one. Particle Swarm Optimization (PSO) can also be regarded as an optimization algorithm by message-passing, which makes it possible to combine Log-BP algorithm with PSO. PSO was introduced into Log-BP algorithm by regarding...
The swarm intelligence is attracted by scholars in many fields by its special advantages, and its theories and applications have been developed greatly. As a representative method of swarm intelligence, ant colony optimization (ACO) is used widely because of its realization simply, positive feedback and distribution. The review of the new applications for ACO and its prospect are given in this paper.
In the application of Particle Swarm Optimization (PSO) for the problem of economic load dispatch (ELD) in power plant There are some problems such as premature convergence of PSO, how to deal with constraints of the problem are need to be addressed. An improved PSO with the constraints partially solved combined with penalty function were introduced in this paper, the improved PSO refined in constraints...
An improved particle swarm optimization scheme for codebook design is proposed in this paper. By sorting the training vector, we select the initial codebook to enhance the diversity of search, and add stagnant judging algebra to prevent the algorithm falling into a local optimum. The simulation results prove that the improved method is reasonable.
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