Search Results - (( evolution classification using algorithm ) OR ( _ application using algorithm ))
Search alternatives:
- evolution classification »
- classification using »
- using algorithm »
-
1
Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
Get full text
Get full text
Get full text
Thesis -
2
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
Get full text
Get full text
Thesis -
3
Intersection Features For Android Botnet Classification
Published 2019“…The Chi Square was used to select the most significant permissions, then the classification algorithms like Naïve Bayes and Decision Tree were used to classify the Android apps as botnet or benign apps. …”
Get full text
Get full text
Get full text
Article -
4
EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization
Published 2019“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
Get full text
Get full text
Get full text
Article -
5
Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
Get full text
Get full text
Get full text
Conference or Workshop Item -
6
Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
7
A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection
Published 2019“…To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
Get full text
Get full text
Get full text
Article -
8
Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
Get full text
Get full text
Thesis -
9
Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. The best combinations were selected to train individual ARTMAPs as voting members, and the final class predictions were determined using probabilistic ensemble voting strategy. …”
Get full text
Get full text
Conference or Workshop Item -
10
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
Get full text
Get full text
Thesis -
11
Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
Get full text
Get full text
Thesis -
12
Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
Get full text
Get full text
Get full text
Proceeding Paper -
13
Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
Get full text
Get full text
Article -
14
Artificial fish swarm optimization for multilayer network learning in classification problems
Published 2012“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
Get full text
Get full text
Get full text
Article -
15
Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems
Published 2012“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN. …”
Get full text
Get full text
Get full text
Article -
16
Deep learning detector for pests and plant disease recognition
Published 2020“…The goal of this project is to develop a framework that can classify the class of a plant, and detect areas of the plant leaf already affected by diseases, and eventually deploy the framework on a mobile application. In order to find a suitable meta-architecture for the aim of the project, we use the combination of Single Shot MultiBox Detector and MobileNet (SSD MobileNet) where Single Shot MultiBox Detector (SSD) is the algorithm that takes a single shot to detect multiple objects within an image, and mobilenet is a neural network for recognition and classification. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
17
Analysis on target detection and classification in LTE based passive forward scattering radar
Published 2016“…The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.…”
Get full text
Get full text
Get full text
Article -
18
Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
Get full text
Get full text
Book Section -
19
-
20
ios Mobile Malware Deep Analysis And Classification For Social Media And Online Banking Exploitation
Published 2024thesis::master thesis
