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Clonal Selection-Based Neural Classifier

A. Lanaridis, V. Karakasis, A. Stafylopatis
2008 2008 Eighth International Conference on Hybrid Intelligent Systems  
The Clonal Selectionbased Neural Classifier (CSNC) uses the basic concepts of clonal selection to evolve MLPs, which are represented as real-valued linear antibodies.  ...  This work is a first attempt of applying the clonal selection principle to the training of Multi-Layer Perceptrons (MLPs).  ...  In this paper, we present a first approach to applying the clonal selection principle to the training of a neural multi-classifier.  ... 
doi:10.1109/his.2008.82 dblp:conf/his/LanaridisKS08 fatcat:b732vzuemzbtbizsmgpjis4sny

Heart Disease Prediction Using Integer-Coded Genetic Algorithm (ICGA) Based Particle Clonal Neural Network (ICGA-PCNN)

Silvia Priscila S., Hemalatha Dr.M.
2018 Bonfring International Journal of Industrial Engineering and Management Science  
Then Multilayer feed forward neural network (MFNN) is used as a classifier to classify the ECG signal, where the weight and the biased are trained using the Particle based clonal selection.  ...  Hence this paper proposes an Integer-Coded Genetic Algorithm (ICGA) based Particle Clonal Neural Network (ICGA-PCNN) for classifying the different ECG arrhythmias.  ...  Then Multilayer feed forward neural network (MFNN) is used to classify the ECG signal, where the weight and the bias are trained using the Particle clonal neural network selection.  ... 
doi:10.9756/bijiems.8394 fatcat:tssst7kxjjeb5d77oylffvbguq

POLSAR image classification using BP neural network based on Quantum Clonal Evolutionary Algorithm

Bin Zou, Huijun Li, Lamei Zhang
2010 2010 IEEE International Geoscience and Remote Sensing Symposium  
In PROCUDURE OF BP NEURAL NETWORK CLASSIFIER BASED ON QUANTUM CLONAL EVOLUTIONARY ALGORITHM In this paper, BP neural network based on quantum clonal evolutionary algorithm is used as a classifier for  ...  There are three steps in clonal operator: cloning, mutation, selection.  ... 
doi:10.1109/igarss.2010.5653650 dblp:conf/igarss/ZouLZ10 fatcat:32xg2pkv5jh2bknpnlc4vlrquq

Comparison Of K Nearest Neighbours And Regression Tree Classifiers Used With Clonal Selection Algorithm To Diagnose Haematological Diseases

Burcu Çarklı Yavuz, Tuba Karagül Yıldız, Nilüfer Yurtay, Ziynet Pamuk
2014 AJIT-e Online Academic Journal of Information Technology  
In classification problems it has been seen that kNN classifier is often used with the clonal selection algorithm.  ...  While accuracy in memory---based classification is found as 96%, accuracy in regression tree method classification is 98.73%.  ...  Clonal selection algorithm is often used with kNN classifiers.  ... 
doi:10.5824/1309-1581.2014.3.001.x fatcat:pcz3bbwkmffojhijyjc5jinhfe

Recognition of Odia Handwritten Digits using Gradient based Feature Extraction Method and Clonal Selection Algorithm

Puspalata Pujari, Babita Majhi
2019 International Journal of Rough Sets and Data Analysis  
This article aims to recognize Odia handwritten digits using gradient-based feature extraction techniques and Clonal Selection Algorithm-based (CSA) multilayer artificial neural network (MANN) classifier  ...  The results obtained from the experiment are compared with a genetic-based multi-layer artificial neural network (GA-MANN) model. The recognition accuracy of the CSA-MANN model is found to be 90.75%.  ...  Clonal selection based multilayer artificial neural network model Figure 2 . 2 Figure 2. shows a set of Odia handwritten digit (0-9) Figure 3 . 3 Figure 3.  ... 
doi:10.4018/ijrsda.2019040102 fatcat:r2pvfjmkm5dibostzguif5svju

Licence Plate Character Recognition Using Artificial Immune Technique [chapter]

Rentian Huang, Hissam Tawfik, Atulya Nagar
2008 Lecture Notes in Computer Science  
The use of Clonal Selection Algorithm (CSA) is composed of two main stages: (1) dynamic training samples; and (2) a choice of the best antibodies based on the three main clonal operations of cloning, clonal  ...  mutation and clonal selection.  ...  In this work, an AIS character recognition technique based Clonal Selection Algorithm is presented for solving LPR problem.  ... 
doi:10.1007/978-3-540-69384-0_87 fatcat:gcwrfac2q5dphojjkqsx4d3bqa

Immuno-Computing-based Neural Learning for Data Classification

Ali Al Bataineh, Devinder Kaur
2019 International Journal of Advanced Computer Science and Applications  
The paper proposes two new algorithms based on the artificial immune system of the human body called Clonal Selection Algorithm (CSA) and the modified version of Clonal Selection Algorithm (MCSA), and  ...  Each antibody is evaluated based on its affinity and clones are generated for each antibody.  ...  In this paper, two neural-network learning algorithms based on the human immune system, namely, Clonal selection Algorithm (CSA) and Modified Clonal Selection Algorithm (MCSA) are proposed to adjust the  ... 
doi:10.14569/ijacsa.2019.0100632 fatcat:zbezrexymndbhfic5xatvra234

A Novel Hybrid CNN-AIS Visual Pattern Recognition Engine [article]

Vandna Bhalla, Santanu Chaudhury, Arihant Jain
2015 arXiv   pre-print
A layer of Clonal Selection is added to the local filtering and max pooling of CNN Architecture.  ...  Convolutional Neural Networks (CNN) have time and again proved successful for many image processing tasks primarily for their architecture.  ...  The architecture of our hybrid CNN-AIS model was designed by adding an additional layer of Artificial Immune System (AIS) based Clonal Selection (CS) in the traditional Convolutional Neural Network (CNN  ... 
arXiv:1503.03270v1 fatcat:xukrczsxqbdibaa4jh6uwv6m5e

Classification techniques based on Artificial immune system algorithms for Heart disease using Principal Component Analysis

Kirti Bala Bahekar
2021 International Journal of Scientific Research in Science Engineering and Technology  
In this paper, artificial immune stimulated classifiers as supervised learning methods are used for classifying Heart disease datasets.  ...  The performance of the classifiers strongly depends on the datasets used for learning.  ...  Classification can be done by using various methods like decision tree, rule-based methods, memory-based methods, Bayesian network, neural network, etc.  ... 
doi:10.32628/ijsrset207542 fatcat:yvwj7pgknngffeiv2y5ps72tty

A Novel Hybrid CNN-AIS Visual Pattern Recognition Engine [chapter]

Vandna Bhalla, Santanu Chaudhury, Arihant Jain
2015 Lecture Notes in Computer Science  
A layer of Clonal Selection is added to the local filtering and max pooling of CNN Architecture.  ...  Convolutional Neural Networks (CNN) have time and again proved successful for many image processing tasks primarily for their architecture.  ...  The architecture of our hybrid CNN-AIS model was designed by adding an additional layer of Artificial Immune System (AIS) based Clonal Selection (CS) in the traditional Convolutional Neural Network (CNN  ... 
doi:10.1007/978-3-319-19941-2_21 fatcat:xtah3cyg6nfkvko4m3rmi7v2pq

Artificial immune pattern recognition for structure damage classification

Bo Chen, Chuanzhi Zang
2009 Computers & structures  
The training process is designed based on the clonal selection principle in the immune system.  ...  The selective and adaptive features of the clonal selection algorithm allow the classifier to evolve its pattern recognition antibodies towards the goal of matching the training data.  ...  The training process is designed based on the clonal selection principle in the immune system.  ... 
doi:10.1016/j.compstruc.2009.08.012 fatcat:akhxsnn575dl5jcx62ocpkjo6u

Brake fault diagnosis using Clonal Selection Classification Algorithm (CSCA) – A statistical learning approach

R. Jegadeeshwaran, V. Sugumaran
2015 Engineering Science and Technology, an International Journal  
The selected features were then classified using CSCA. The classification accuracy of such artificial intelligence technique has been compared with other machine learning approaches and discussed.  ...  The Clonal Selection Classification Algorithm performs better and gives the maximum classification accuracy (96%) for the fault diagnosis of a hydraulic brake system.  ...  A report illustrated a fuzzy and neural network based fault diagnosis system for a centrifugal pump to classify faults at early stages [14] .  ... 
doi:10.1016/j.jestch.2014.08.001 fatcat:ilighzxdbvc7hcfo53x6va7ofm

Study on the Application of Artificial Immunity in Virus Detection System

Daping DENG, Xiaohong DENG
2011 International Journal of Engineering and Manufacturing  
, we analyze the disadvantages of traditional virus detection methods and new functions of artificial immune technology, and then review some typical algorithms of the existing virus detection system based  ...  Fig. 1 . 1 A general model of virus detection systems or methods based on artificial immunity Fig. 2 . 2 Negative selection process Fig. 3 . 3 Single layer neural classifier  ...  Among those methods, there are three basic models based on AIS principles: negative selection algorithm, clonal selection algorithm and the immune network model.  ... 
doi:10.5815/ijem.2011.05.07 fatcat:slg4eftgi5fg5jstdc62ykexry

Compare Between Genetic Algorithm and Clonal Selection Algorithm To Pattern Recognition Latin's Numbers

Maha Mohammed
1970 Journal of education and science  
This work involves the use some of Artificial intelligence techniques algorithms which are genetic algorithm and artificial immune system algorithm-clonal selection algorithm.  ...  Both above algorithms are based on optimization principle in getting the results.  ...  Pattern discrimination can be classified into three types: the distinction of statistical patterns, the distinction of syntactic patterns, and the differentiation of neural patterns [3, 4] .  ... 
doi:10.33899/edusj.1970.162121 fatcat:ro2pq3njobhw3onb3yaxq6ah6e

IN-MACA-MCC: Integrated Multiple Attractor Cellular Automata with Modified Clonal Classifier for Human Protein Coding and Promoter Prediction

Kiran Sree Pokkuluri, Ramesh Babu Inampudi, S. S. S. N. Usha Devi Nedunuri
2014 Advances in Bioinformatics  
We propose a classifier that is built with MACA (multiple attractor cellular automata) and MCC (modified clonal classifier) to predict both regions with a single classifier.  ...  This classifier is trained and tested with MMCRI datasets for protein coding region prediction for DNA sequences of lengths 252 and 354.  ...  Modified Clonal Classifier with MACA Simplified Modified Clonal Algorithm (1) Generate initial antibody population (AIS-MACA rules) randomly and call it Ab.  ... 
doi:10.1155/2014/261362 pmid:25132849 pmcid:PMC4123571 fatcat:by5bol6foje7nb4haizr7gv5oa
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