Adoption of Back Propagation Network Improved by Particle Swarm Optimization in Network Intrusion Detection
نویسندگان
چکیده
منابع مشابه
Authorship attribution of source code by using back propagation neural network based on particle swarm optimization
Authorship attribution is to identify the most likely author of a given sample among a set of candidate known authors. It can be not only applied to discover the original author of plain text, such as novels, blogs, emails, posts etc., but also used to identify source code programmers. Authorship attribution of source code is required in diverse applications, ranging from malicious code trackin...
متن کاملImproved Binary Particle Swarm Optimization Based TNEP Considering Network Losses, Voltage Level, and Uncertainty in Demand
Transmission network expansion planning (TNEP) is an important component of power system planning. Itdetermines the characteristics and performance of the future electric power network and influences the powersystem operation directly. Different methods have been proposed for the solution of the static transmissionnetwork expansion planning (STNEP) problem till now. But in all of them, STNEP pr...
متن کاملOptimal Rotor Fault Detection in Induction Motor Using Particle-Swarm Optimization Optimized Neural Network
This study examined and presents an effective method for detection of failure of conductor bars in the winding of rotor of induction motor in low load conditions using neural networks of radial-base functions. The proposed method used Hilbert method to obtain the stator current signal push. The frequency and signal amplitude of the push stator were used as the input of the neural network and th...
متن کاملBig Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce
A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural netwo...
متن کاملParticle Swarm Optimization Based on Back Propagation Network Forecasting Exchange Rates
This research constructs a new forecasting model. Particle Swarm Optimization (PSO) is utilized to select the optimal input layer neurons, and then predict exchange rates by the Back Propagation Network (BPN), which called PSOBPN model. The model is applied to forecast exchange rate NTD/USD. We hope to improve traditional neural network that utilized the try-and-error method to find out the bet...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2020
ISSN: 1742-6588,1742-6596
DOI: 10.1088/1742-6596/1650/3/032048