pso

The experiment results showed that this approach has advantages of both PSO and FLANN, meanwhile it has better precision.

Although very easy to implement, this hybrid SM-PSO is an efficient way to locate global optima of continuous multimodal functions.

It used to solve the problem that Particle Swarm Optimization(PSO) easily falls into a local extremum.

this document is mainly targeted at PSO algorithm in Matlab environment application to the preparation of that document m!

And, in FNN weight training, improved PSO in the convergence rate and the ability to jump out to local optimum algorithm is better than BP.

To perform the parallel optimization, the comparison used in tournament selection was employed to compare the searched solutions of the PSO.

Task assignment problem is a typical NP problem. Particle Swarm Optimization (PSO) algorithm was used to solve task assignment problem.

Finally, this optimization algorithm is proved to be effective by an example.

To this problem, this paper proposed one kind of method to choose the parameters of the SVM by particle swarm optimization algorithm (PSO).

This variant of PSO enables the diversity of the swarm to be preserved to discourage premature convergence.

This new algorithm applies particle swarm optimization (PSO) to design the CNN templates to identify the edge of a nucleated cell.

The PSO attribute reduction algorithm ought to improve the efficiency, however, it has the premature convergence problem.

Subsequently, this paper focuses on PSO optimization model and its applications in RFID Tags and Antenna Simulation Deployment System.

Particle Swarm Optimization (PSO) algorithm is a powerful method to find the extremum of a continuous numerical function.

It transformed the parameter selection problem into functional optimization problem by creating a function of the PSO property parameters.

Uses multi- populations cooperation optimization algorithm which PSO develops, good article. May have a look to use.

Particle swarm optimization (PSO) is a good inversion method with characterizing simple algorithm, fast convergence, and easy operation.

Another is to examine faults of asynchronous Motors in terms of BP neural network based on Particle Swarm Optimization(PSO).

The simulation results show that the improved PSO algorithm can solve the high-dimensional numerical optimization problem effectively.

The computational results show that the PSO is a viable and effective approach to solve the semiconductor furnace batch scheduling problem.

Aiming to solve out the pre-mature convergence phenomenon, the chaos mutation is introduced into PSO for improving global optimal ability.

Then, the problem was solved by particle swarm optimization algorithm (PSO) after elimination of the constraint equations.

Results show that the improved PSO algorithm has a great improve in global search capability and solution precision.

The theoretical analysis and experimental results indicate that the proposed niche PSO algorithm is feasible and effective.

Summary of Background Data. PSO is a technique popularized in the lumbar spine primarily for the correction of fixed sagittal imbalance.

Application examples show that it is feasible to apply the improved PSO to the weight solution of power load combination forecasting model.

At last, individual decision-making PSO is applied into solving nonlinear equations problem, simulation results show they are more superior.

By adopting a dynamic inertia gene and condensed network structure, this article improve BP-PSO algorithm, efficiently solve these problems.

This paper adds mutation operator to adaptive PSO and apply it in the lymphoma morphology parameter classifier problems.

Particle swarm optimization (PSO) algorithm is easy to be trapped into local minima in optimizing multimodal function.

PSO clustering algorithm is known to have simple parameters and fast convergence, but there are also local optimal problems.

Considering the stronger search ability of Particle Swarm Optimization(PSO), this paper introduces a PSO covering algorithm.

During the search process of PSO, the chaotic local optimizer was introduced to raise its resulting precision and convergence rate.

Adaptive perceptive ability is assigned to particles in PSO for balancing their global and local searching and avoiding prematurity.

The parameters and thresholds of classifiers are optimized by improved Particle Swarm Optimization(PSO) algorithm.

Finally, we use an engineering example with PSO arithmetic to realize optimization of the machine tool basic shaft.

If some particles trended to local extremum in PSO algorithm implementation, the particle velocity was updated and re-initialized.

Particle Swarm Optimization (PSO for short) is a evolutionary algorithm with simple operations and few parameters.

Emulation experiments demonstrated that the modified algorithm improves the PSO's global search capability remarkablely.

This paper presents a survey of the PSO on Project of Power Grid Construction and Irrigation, and provides some outlook.

We design the mathematical model of auto-generating test paper algorithm and improved the traditional PSO inertia weight to non-liner form.

Deriving from the behavior of birds of prey PSO with genetic algorithm is similar to an iterative optimization-based tools.

In this section, we describe the formulations of the PSO algorithm for Auto-generating test paper algorithm.

A method to evaluate spatial straightness errors adopting particle swarm optimization (PSO) is proposed.

Genetic algorithm (GA) and particle swarm optimization (PSO) are taken for computing the error and compared with BFGS method.

The reasons of premature convergence of Particle Swarm Optimization (PSO) Algorithm were analyzed.

It uses Particle Swarm Optimization(PSO) algorithm to search the optimized partial contents which is the most similar in two documents.

Realization method of PSO and APSO is designed including the code design, iterative algorithm design and inertia weight design, etc.

Using PSO algorithm in paper's generating is a discrete solution problem, which extends PSO algorithm's application.

A new method, particle swarm optimization(PSO) algorithm, is adopted to locate the non-circular critical slip surfaces of slopes.

We proposed that using PSO to optimize the initiate parameters of the neural network for there were no law to refer.

By comparing and analyzing the results of several standard test functions, the excellent performance of PSO is proved.

Test result indicates that the improved PSO advanced distinctly in performance like convergence speed and convergence rate. 2.

The component and heat treatment parameters are optimized by Particle Swarm Optimization(PSO).

For optimization of algorithm, Particle Swarm Optimization (PSO) was utilized.

We applied PSO-BP to evaluate the environmental effect of an agricultural project.

Particle Swarm Optimization (PSO) algorithm for solving multiple Nash equilibrium solutions of bimatrix game is presented in this paper.

Theoretical analysis proves that the M-PSO algorithm keeps convergence.

Conclusion: Xiaoyin-ointment is proved to be effective in the treatment of pso. . .

We solve the upper model by PSO algorithm and lower model by Affine Scaling Interior Point Method.

A novel hybrid particle swarm optimization (PSO) based on adaptive population mutation and individual annealing operation was developed.

It presents a method of optimum placement of sensors in gearbox based PSO algorithm to solve the problem of sensors layout and localization.

We also propose to use a hybrid version of PSO embedding a local optimizer to enhance the performance.

Third, this paper does research on the ability of local search and converging speed of PSO in later period.

Step 1: Set the maximum of iterations taken and Initialize the PSO parameters, , . Initialize a population of particles.

"I can't believe you are 17, " said William Caballero , principal horn player of the Pittsburgh Symphony Orchestra (PSO).

PSO is utilized to optimize the RBFNN training process, which has improved the training speed of the model.

PSO is the need to go through more cycles before convergence to the global optimum.

In the method, peak is used as fitness function, and the PSO algorithm is used to withdraw blindly from several signals.

PSO is utilized to optimize the RBFNN training process, which has improved the credibility and reliability of model.

According to the trait of power load, this paper proposes a PSO based fuzzy neural network model for short-term load forecasting.

Particle Swarm Optimization (PSO) is a new evolutionary computation technique based on swarm intelligence.

It is proved that the performance of improved PSO can solve this problem efficiently.

Experimental results indicate that the ANN based on improved PSO can reduce the times of training and MSE effectively.

This paper presents a new polygonal approximation approach based on the particle swarm optimization (PSO) algorithm.

To test performance, it's compared with gradient descent algorithm, PSO algorithm and QPSO algorithm.

An optimization scheme of analog filter design based on the particle swarm optimization (PSO) algorithm are proposed.

The article use the space which include all the PSO results to train the BP.

Segmental sagittal correction appears to vary based on the region of the thoracic spine the PSO is performed.

It is supposed that the hybrid PSO will be an effective method for discrete combinatory problems.

It sets up intelligent fault diagnosis based on PSO with dynamic accelerating constants and adaptive velocity.

The result is also very promising in finding the optimal parameters of PSO by differential evolution.

Firstly, introducing genetic PSO algorithm into the field of gene selection.

Finally, the PSO was used to find the correct skew angle in the whole searching space from -90 to 90 degree.

Then, the data set is classified by PSO fuzzy clustering algorithm to adaptively detect the image edge points so as to extract an edge.

Secondly, the estimation method of the target satellite's orbital elements is proposed based on PSO.

Based on analyzing algorithm of particle swarm optimization(PSO), the algorithm of vector particle swarm optimization(VPSO) is proposed.

Particle swarm optimization (PSO) is described and analyzed; and it is applied to calibrate Xin'anjiang model.

This paper presents a multi-objective quantum Particle Swarm Optimization(PSO) based on game theory.

This paper applies PSO algorithm to pretreatment of face detection. In order to improve efficiency and accuracy of face detection.

In order to speed up convergence, this paper implants the memory mechanism in the traditional binary PSO.

This work concentrates on three multi-objective shop schedulings based on PSO algorithm.

In order to improve performances of fuzzy neural networks (FNN), a method of training FNN using particle swarm optimizers (PSO) is proposed.

In order to enhance the performance of the PSO algorithm identification, an MPSO algorithm is also proposed.

So, we proposed a multi-objective PSO based on adaptive crowding grid(ACG-MOPSO for short).

Simulation results show that APSO not only effectively alleviates the problem of premature convergence, but also has fast convergence speed.

PSO algorithm which to target function in the source can make changes!

In order to quickly and accurately distinguish 12 insulation faults, 12 LS-SVM classifiers based on adaptive PSO are built.

Application of a Multi-stage PSO Neural Network System for Handwritten Character Recognition

The Research of a Hybrid Clustering Algorithm Incorporating PSO into k- Means Algorithm

PSO Based Predicted Control and Its Application to Temperature Control of Polypropylene Reactor

Application of PSO Based Neural Network in Suppression of Stochastic Pulse Interference for Partial Discharge Monitoring in Large Generators

Improved PSO Used in Optimized Configuration of Compensation Capacitor

Particle swarm optimization (PSO) include 3 parts: the first part was the current flight status for the particles;

Study of the application of PSO algorithms for nonlinear problems

Second-Order Polarization Mode Dispersion Self-adaptive Compensation Experiment Using PSO Algorithm

A Study of Application of An Improved PSO Algorithm in BP Network

Improved PSO algorithm and its application in short-term generation scheduling

an improved particle swarm optimization (PSO) was used to find correction steps of nodes;

Improved PSO and Its Application to Load Distribution Optimization of Hot Strip Mills

Improved PSO and its application in crystallizer liquid level control system

PSO-Based Water Consumption Determination for Secondary Cooling Zone During Continuous Casting

PSO-BP Network Modeling and Its Application to Cushioning Packaging Design

Study of Physical Distribution Routing Optimization Problem Based on Hybrid PSO Algorithm

Application of PSO in Inverse Calculation of Hydrogeological Parameters

Improved PSO neural network system for automatic detecting fertility of hatching eggs

PSO-Based Optimization of Signal Timing and Simulation for Isolated Intersection

Generate Fuzzy Rules of Controller Parameters Automatically Using PSO

Optimization of Cluster-based Routing Protocols in Wireless Sensor Network Using PSO

Research on PSO Algorithm Applied in Defect Identification Using Thermal Imager

Optimization Design of Hydro Turbine Governor Parameters by PSO Algorithm

Application of PSO algorithm in sensor nonlinear self-rectification

General Hybridized PSO with Chaos for Fast Infrared Image Segmentation Method

Application of PSO Algorithm with Compression Factor in Gear-box Faults Diagnosis

Research on the unlimited resource leveling optimization with PSO

PSO Model in Analysis of Design Confidence Level for Asphalt Pavement Structure

Application of PSO for Parameter Estimation of Nonlinear System Model

Parameter identification of dynamical system for microorganism in batch fermentation based on PSO algorithm

PSO Algorithm Based Optimal Supply Function Model for Power Producer

Application of PSO and GA in beamforming of an array antenna

PSO for Optimal Design of Light Fill Expressways

A new method to control fuel flow of aircraft engine's starting process based on PSO Algorithm

Optimization and Simulation of Continuous Casting Secondary Cooling Based on Enhanced PSO Algorithm

PSO Based Temperature Model Optimization

Application of PSO algorithm in design of automated control system

PSO-Based Optimization Design for Fuzzy controllers

Application of PSO to improve multiple linear regression

Application of PSO Algorithm in Mobile Networks Planning

Optimization of time-sharing power supply for zinc electrolytic process based on improved PSO algorithm;

A PSO Algorithm for Optimized Combinational Design of Parameters in Nonlinear Circuits

A Network and Its Simulation for Trajectory Recognition Based on PSO Algorithm

PSO and SVM-Based Financial Crisis Warning Model for Listed Companies

Simultaneous Feature Selection and SVM Parameters Optimization Algorithm Based on Binary PSO

Logical layered-and-delayed PSO algorithm and application based on formalization description

Exact Evaluation of Damping and Frequency by Laplace Wavelet and PSO

Improved PSO Algorithms for Unit Commitment of Power System

An Analysis for a Particle's Trajectory of PSO Based on Difference Equation

Application of PSO Algorithm in Wavelet Neural Network

Optimal Design for Cascaded Mach-Zehnder Interferometer Based Filter Using PSO

An improved PSO algorithm for solving MINLP problems with equality constraints

Applying PSO to virtual actor's facial expression modeling

Calculation on Laser Scattering Phase Function of Water PSO in Wet Steam

Analysis of the Bidding Strategy of Power Producers with Non-cooperative Game Theory Based on PSO

Application of Improved PSO in Control of Ferment Process

Generation Analysis of Power Station by the Optimum Operation Model Based on Improved PSO

Nonlinear Programming PSO Algorithm Based on a Line Search and Dynamic Adjustment

Fast Texture Synthesis Algorithm Using PSO

Study on Function Optimization and Model Reduction Based on a Class of Hybrid PSO Algorithm

Structural reliability and sensitivity analysis of random variables based on PSO

The Prediction of the Price of Coal and Electricity Based on PSO and BP Neural Network

Optimization of Ordnance Urgent Transportation Decision Based on PSO

Optimal Planning of Substation Locating and Sizing Based on Refined Multi-team PSO Algorithm

Inertia Parameter and Swarm Size Selection of PSO

Transmission Network Optimization Planning Based on Hybrid PSO

Analysis of System Reliability Optimization Based on PSO Algorithms

Algorithm based on immune PSO ensemble for predicting RNA secondary structure

The Strategy of Parameters-selection for PSO Based on Differential Evolutions

Multimodal Function Optimization Algorithm Based on Niche PSO

Study on the short-time rainfall prediction model of neural ensemble based on PSO algorithms

A PSO Based Approach to Optimize PID Parameters

Research and Application on Damage Detection of Structure Based on PSO Algorithm

An processing method of measured data from scroll wrap using a three-coordinate machine based on PSO

A New PSO Algorithm Based on the Statistical Regulation of the Particle Swarm

The Books Purchase Duplicate Amount Optimum Decision Based on PSO Algorithm

A PSO with dimension mutation operator

Optimal design for two degree-of-freedom PID controller based on PSO algorithm

Enterprise credit risk evaluation model based on GA-PSO optimize algorithm

Optimal load distribution for speediness in power plants based on modified PSO

Optimization for PID Control Method on Hydraulic Servo Control System Based on PSO

Application of artificial neural network based on PSO in dynamic alliance

Load Distribution Optimization of Tandem Cold Mill Based on PSO Algorithm

The pattern synthesis of antennas based on a modified PSO algorithm

PSO schedule algorithm for DAG task model

Optimization of ship degaussing system based on multi-population PSO

Generation expansion planning of hydro-thermal mixed power system based on C-PSO

Quick mountain clustering based on improved PSO algorithm

Application of neural networks based on PSO in the lithology recognition

Generation Expansion Planning of Hydro-thermal Power System Based on SA-PSO

Method of membership function based on fuzzy theory by PSO algorithm optimized

Image segmentation algorithm based on the PSO and improved Snake model

Predicting Chaotic Time Series Using a Product Unit Network Based on PSO

Short-term load forecast in Power system based on PSO optimizing algorithm

Neural Network Ensembles Based on Improved PSO Algorithm

A Medical Image Registration Method Based on Mixed PSO Algorithm

Command Optimization for CNC Camshaft Grinding Based on PSO

A nonlinear model predictive control based on PSO algorithm

The Optimization of Aircraft Flight Control System Based on PSO

PID parameters tuning based on improved PSO algorithm

Research on PSO Optimize Algorithm Based on Path of Moving Object

Research on optimization of well track based on PSO algorithm

A RBF Neural Network Learning Algorithm Based on Improved PSO

Study on evolutionary games based on PSO-neural networks

A short-term load forecasting approach based on PSO support vector machine

A Method of Median Filter Based on Fuzzy Theory by PSO Algorithm Optimized

Application of Neural Network Based on PSO in Data Fusion of Sensor

Image segmentation based on PSO algorithm

PSO based on multiple target optimization

The application of grey model based on PSO in load forecasting

Image segmentation with Otsu based on improved PSO

UCAV Path Planning Based on Modified PSO Algorithm

Research on Decision Tree Method Based on Improved PSO

Structural Damage Detection Based on PSO

Ellipsometry Data Inverting Based on PSO

A PSO Algorithm Based on Colony Fitness Variance

A Recommender System for the Real Estate Based on PSO Algorithm

Optimization for Parameter of PID Based on PSO

Selection of Soccer Robot Action Based on PSO