[PDF] Top 20 Spam detection using hybrid of artificial neural network and genetic algorithm

Spam detection using hybrid of artificial neural network and genetic algorithm

... Many researches are founded in applying Artificial Neural Network (ANN). The major cons of ANN are that it needs considerable time to select the parameter and network training. On the other ... See full document

23

Optimization of Hybrid Journal Bearing using Artificial Neural Network and Genetic Algorithm

... hole-entry hybrid journal bearing having transverse roughness pattern is developed using Artificial Neural Network (ANN) and Multi Objective Genetic Algorithm ...of ... See full document

9

A Hybrid Model using Artificial Neural Network and Genetic Algorithm for Degree of Injury Determination

... the hybrid model which is Artificial Neural Network and Genetic Algorithm techniques by using critical features obtained from previous studies to increase the accuracy of ... See full document

9

Spam detection in email body using hybrid of artificial neural network and evolutionary algorithms

... of spam emails has ...impact spam, for the automatically spam detection technique which are responsible to eliminate such spam email from a user email ...consideration spam ... See full document

29

Mitigating Economic Denial of Sustainability (EDoS) in Cloud Environment using Genetic Algorithm and Artificial Neural Network

... out using Nash equilibrium which blocks the EDoS ...services using hybrid filtering ...Lion algorithm is an nature inspired optimization algorithm which is used to find out the EDoS ... See full document

7

Estimation of LLE Data for Binary Systems of N-Formylmorpholine with Alkanes Using Artificial Neural Network–Genetic Algorithm (ANN–GA) Model

... feed-forward artificial neural network (ANN) models were developed for the three ...as network inputs, and the temperature was the output variable. Genetic algorithm (GA) method ... See full document

16

An evolutionary algorithm based Feature extraction and selection to Persian and Arabic Handwritten Recognition

... answer using population evolution and choosing the ...paper, artificial neural network has been used as classifier function for evaluating generated population by genetic ... See full document

5

Estimation of groundwater level using a hybrid genetic algorithm-neural network

... Back-propagation (BP) algorithms are the most popular training algorithms that are widely used due to their simplicity and the application for training FF-NN (Kulluk, 2013). In FF-BP networks, which are considered in ... See full document

13

Towards Solving Travelling Salesperson Problem using Hybrid of Genetic Algorithm and Lin Kernighan Algorithm: A Comparative Evaluation with Neural Network Model

... solution. Genetic algorithm combined with another local search algorithm shows more efficient result could be ...of genetic algorithm with a local search algorithm called ... See full document

9

A Hybrid of Artificial Bee Colony, Genetic Algorithm, and Neural Network for Diabetic Mellitus Diagnosing

... the network will be updated based on (6). The network uses only one set of initial weights and based on the error rate at the output stage, and the learning rate the new set of weights will be calculated ... See full document

10

Intrusion Detection using Artificial Neural Network and Swarm Intelligence Algorithm

... a network against ...or network and investigates them for perceiving interruptions to ensure the PC ...the network packet to analyse and look for intrusive pattern, while some of these features are ... See full document

9

A New Method for Intrusion Detection Using Genetic Algorithm and Neural network

... A hybrid method based on hierarchical clustering algorithms as well as a function that selects a number of important and simple features and ultimately combines them with a variety of vector-based ...the ... See full document

10

Deep Learning Approach Model for Vehicle Classification using Artificial Neural Network

... of detection of vehicles includes the object detection by considering the vehicles as the primary ...parking using surveillance cameras, the detection process can be ...and hybrid ... See full document

7

Disease Classification using ECG Signal Based on PCA Feature along with GA & ANN Classifier

... on Artificial neural network and the Genetic ...Disease Detection System based on GA, and ANN, in which detection is based on performance parameters like precision, Recall, F- ... See full document

7

Bearing Fault Detection Using Artificial Neural Networks and Genetic Algorithm

... condition using vibration sig- nals through three types of ANN ...optimized using a GA-based ...illustrated using the vibration data of an experimental setup with normal and defective ... See full document

12

Exploration of Anomaly Based Intrusion Detection System: A Security Framework

... intrusion detection system are genetic algorithm, apache storm, neural network, artificial immune system, genetic clustering method and Linear Discriminant Analysis & ... See full document

6

MRI brain tumor detection using artificial neural network

... Brain tumor is one of the major causes for the increase in mortality among children and adults. A tumor is a mass of tissue t grows out of control of the normal forces that regulates growth (Pal and Pal, 1993). The ... See full document

7

Spam NSGA II NvBys: An efficient hybrid approach for email spam filtering

... [13]. Spam filter design problem is naturally multi-objective. Given a spam filter, stopping as many spam e-mails as possible is in direct conflict with preventing the filtering of legitimate e- ... See full document

8

Comparative Analysis of ANN-ICA and ANN-GWO for Crop Yield Prediction

... competitive algorithm is a well-known optimization algorithm [11] proposed by Atashpai Gargari and Lucas ...competitive algorithm [13] in which the countries classified into two groups based on their ... See full document

5

Detection and Classification of Wear in Rotary Systems based on ANN and GA

... The main problem with the AE technique is noise contamination from the other machine components rather than to the relatively low AE signal magnitudes. Therefore, signal processing is the next important issue after ... See full document

10