A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Filters
Feature Selection Based on BP Neural Network and Adaptive Particle Swarm Algorithm
2021
Mobile Information Systems
Preserved Fulltext
At present, back propagation (BP) neural network and particle swarm optimization algorithm can be well combined with feature selection. ...
On this basis, this paper adds interference factors to BP neural network and particle swarm optimization algorithm to improve the accuracy and practicability of feature selection. ...
feature selection method based on particle swarm optimization algorithm, the optimization algorithm and feature selection are independent of each other, and the particle swarm optimization algorithm is ...
doi:10.1155/2021/6715564
fatcat:ce5q5xk6frdjhgop4wr326zvay
An Improved Particle Swarm Optimization-Powered Adaptive Classification and Migration Visualization for Music Style
2021
Complexity
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Based on the adaptive particle swarm algorithm and error backpropagation neural network, this paper proposes methods for different styles of music classification and migration visualization. ...
It can find better network weights and thresholds so that particles can jump out of the local optimal solutions previously searched and search in a larger space. ...
Acknowledgments is work was supported by the Heilongjiang Province Philosophy and Social Science Research Planning Project, Heilongjiang Traditional Folk Music "North Ten Fan" Heritage and Innovation Research ...
doi:10.1155/2021/5515095
doaj:bc87c4b3f70f42c4b03ecfceab02fb6e
fatcat:xh3sy6idsncjfnlgui5bft7ycu
Design and Application of BP Neural Network Optimization Method Based on SIWSPSO Algorithm
2022
Security and Communication Networks
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
This paper proposes a simplified PSO algorithm based on stochastic inertia weight (SIWSPSO) algorithm to optimize BP neural network. ...
In order to test the effect and applicability of the method, this paper established a quality safety risk warning based on SIWSPSO-BP network and selected the detection data of intelligent door lock products ...
A simplified particle swarm optimization (SIWSPSO) algorithm based on random inertia weight is proposed to explore the optimization method of BP neural network application. e backpropagation neural network ...
doi:10.1155/2022/2960992
fatcat:abh7k2w6xvhxxckykmrsuvmqaa
Dynamic Hidden Layers Selection of ANN Architecture Using Particle Swarm Optimization
2013
International Journal of Engineering and Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
In this paper Particle Swarm Optimization Technique is used. Particle Swarm Optimization (PSO) has applied to variety of optimization problems and it provides good results. ...
Abstrac -The main purpose of this paper is that how to make Artificial Neural Networks (ANN) dynamic in the sense that it can decide that which architecture from given set of architecture has the optimal ...
Zhitao [12] has trained neural network PSO with adaptive inertia weight is presented. The inertia weight is improved on the adaptive base for optimum weights and threshold. ...
doi:10.7763/ijet.2013.v5.540
fatcat:j25jrhxdzfealnhdoqihzkglyu
Woodworking Tool Wear Condition Monitoring during Milling Based on Power Signals and a Particle Swarm Optimization-Back Propagation Neural Network
2021
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
(PSO)-back propagation (BP) neural network algorithm. ...
The PSO-BP neural network algorithm was used to establish the monitoring model of the woodworking tool wear condition. ...
Acknowledgments: This research was supported by the College of Furnishings and Industrial Design of Nanjing Forestry University.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app11199026
fatcat:muz6sf4yxzgezchqds32fa3ujq
Application of BP Neural Network Optimization Based on PSO Algorithm in Energy Development
2018
Chemical Engineering Transactions
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
To study the application effect of BP Neural Network Optimization based on PSO Algorithm in energy development. ...
Adopt certain technical means to analyze the results and characteristics of BP Neural Network based on PSO Algorithm and explore its feasibility in energy development and application. ...
Liu et al. used a BP neural network based on particle swarm optimization (PSO) algorithm (also known as PSO-BP) to predict the high-speed grinding temperature of titanium-based composites. ...
doi:10.3303/cet1867140
doaj:f1ef3ae929f5401282433588e21ed923
fatcat:vmrjbfti25hx5j5vfa3u6oihim
Training of Multilayer Perceptrons with Improved Particle Swarm Optimization for the Heart Diseases Prediction
2017
International Journal of Swarm Intelligence and Evolutionary Computation
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
This paper suggests a new approach for enhancement of the prediction accuracy of Multi-Layer Perceptrons (MLP) neural network using improved Particle Swarm Optimization (IPSO) technique. ...
The experimental results gives comparably better evaluation over gradient based Back-Propagation (BP) learning algorithm. ...
These techniques are generally based on extraction of morphological and temporal features from processing of ECG signals. ...
doi:10.4172/2090-4908.1000156
fatcat:mpt46fqek5cxvadlybxewioz4u
Fault Diagnosis Based on BP Neural Network Optimized by Beetle Algorithm
2021
Chinese Journal of Mechanical Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Then a fault diagnosis model based on BP Neural Network optimized by Beetle Algorithm is proposed to identify the bearing faults. ...
Compared with the Particle Swarm Algorithm, Beetle Algorithm can quickly find the error extreme value, which greatly reduces the training time of the model. ...
Similar to the particle swarm optimization algorithm for BP Neural Network, Beetle Algorithm [25, 26] can also be combined with BP Neural Network (Figure 4 ). ...
doi:10.1186/s10033-021-00648-2
fatcat:nn4ehq6sbjaqtnxnfb5fzxn4oe
Application of Neural Network Integration in Fault Diagnosis
2014
The Open Mechanical Engineering Journal
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
In the generation of individuals in the network integration, a variety of genetic algorithms and particle swarm optimization algorithm are used to train individual networks, thus to improve the precision ...
According to the generation methods of individual neural network and the methods of generating conclusions from integrated neural network, an effective neural network integration system can be constructed ...
[11] researched on the fault feature extraction based on Kernel Principal Component Analysis (KPCA), and proposed a neural network integration method based on KPCA-KFCM, which solved the selection problem ...
doi:10.2174/1874155x01408010081
fatcat:nm67kjmkzbcahff4zuw3ofyc7u
Gases concentration estimation using heuristics and bio-inspired optimization models for experimental chemical electronic nose
2011
Sensors and actuators. B, Chemical
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
and adaptive genetic algorithm, for optimizing back-propagation multilayer perceptron neural network. ...
We describe the performance of a particle swarm optimization technique, an adaptive genetic strategy and a back-propagation artificial neural network approach to perform concentration estimation of chemical ...
Adaptive particle swarm optimization (APSO) The adaptive particle swarm optimization (APSO) algorithm which is based on the standard PSO, was firstly proposed [21] . ...
doi:10.1016/j.snb.2011.08.060
fatcat:5j3rgcswdffw5aj4logduohahq
An improved particle swarm optimization algorithm used for BP neural network and multimedia course-ware evaluation
2016
Multimedia tools and applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
So this paper proposes an improved particle swarm optimization (PSO) algorithm to optimize BP neural network. ...
In this new algorithm, PSO uses improved adaptive acceleration factor and improved adaptive inertia weight to improve the initial weight value and threshold value of BP neural network. ...
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. ...
doi:10.1007/s11042-016-3776-5
fatcat:tdwemmgclfcwbhr5ad4iwyjc4q
Optimizing Back-Propagation using PSO_Hill_A* and Genetic Algorithm
2013
International Journal of Computer Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
BP have the disadvantage of trapped in local minima, slow convergence rate and more error prone. To optimize BP Algorithm, Particle swarm optimization(PSO) and Genetic algorithm(GA) is used. ...
Limitation of PSO_Hill and PSO_A* is overcomes when these algorithms are combined and on the basis of strength of these two algorithm we proposed a new PSO_Hill_A* algorithm which is used to optimize and ...
The application of genetic algorithm on neural network make an hybrid neural network where the weights of the neural network are calculated using genetic algorithm approach. ...
doi:10.5120/12453-9181
fatcat:nwcuslmq6bfpthy7txll5kegnq
Swarm optimization improved BP algorithm for microchannel resistance factor
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this paper, a new swarm optimization improved BP (Back Propagation) algorithm, combination of PSE (Particle Swarm Evolution) and BP, called PSE-BP algorithm, is introduced to train ANN (Artificial Neural ...
The PSE algorithm was firstly proposed by comprehensively learning the principle of gradient descent, genetic algorithm and particle swarm optimization. ...
In GA algorithm, the parents is selected by using roulette algorithm based on the fitness of the individuals in the population. ...
doi:10.1109/access.2020.2969526
fatcat:uqnpq4rwknfdfprro4wt3v6qom
Special issue on machine learning algorithms for internet of things, fog computing and cloud computing
2018
Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The fifth paper, entitled Prediction Algorithm of PM2.5 Mass Concentration Based on adaptive BP Neural Network, by Chen Yegang, used the BP neural network algorithm to predict the quality of PM2.5 and ...
algorithm into the particle swarm optimization with constriction factor. ...
doi:10.1007/s00607-018-0644-3
fatcat:kr3464yrm5daxjju3igawytpvy
Research on a new hybrid intelligent fault diagnosis method and its application
2016
International Journal of Smart Home
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In order to overcome the shortcomings of slow convergence speed and easy falling into the local minimum values of the BP neural network, an improved particle swarm optimization(PSO) algorithm is proposed ...
Then the IMPSO algorithm is selected to optimize the parameters of RBF neural network by encoding the particle and continuous iteration of the IMPSO algorithm in order to obtain the optimal combination ...
Acknowledgments This research was supported by the Science and Technology Program of Dazhou (Research on the key technology of intelligent fault diagnosis for spindle system of large and middle NCM), China ...
doi:10.14257/ijsh.2016.10.7.14
fatcat:c2fum6gidjazljviuv3hbo6jze
« Previous
Showing results 1 — 15 out of 2,188 results